Alcohol Prevention

There is a rich body of literature that deals with intervention approaches for the large population that have problems with alcohol abuse. Alcohol abuse appears to be a grave situation, considering the huge number of adolescents who have a problem with alcohol and substance abuse.Thus, â€Å"[i]n 2002, an estimated 10.7 million American youths, 28.8% of total youths 12–20 years old, were current drinkers† (Society for the Study of Addiction, 2004).The gravity of the problem is underscored by the huge part of the statistics to belong to binge and heavy drinkers. The â€Å"US National Survey on Drug Use and Health in 2002† estimated that 7.2 million adolescents are binge drinkers, while 2.3 million adolescents are heavy drinkers. Heavy drinkers are those who consumed more than four drinks in five different days in the past 30 days.The staggering figures lead to the conclusion that there is serious public health problem among the youth with respect to their alcohol consumption.This problem extends to serious behavioral disorders resulting from alcohol consumption, such as alcoholism. The problem is even more serious because disorders that are related to alcohol abuse are likely to become â€Å"chronic and to persist into adulthood† (Society for the Study of Addiction, 2004).The problem with adolescent alcohol abuse has led to the development of various treatments, both in the private and public healthcare systems. These treatments often range from adolescent to adult care.However, treatment cares often result in relapse in 50-70 percent of affected adolescents. Therefore, there is a need for systematic approaches that are tailored to meet the specific needs and limitations of the target population, which is the youth (Society for the Study of Addiction, 2004).Treatments require appropriate diagnostic criteria in assessing alcohol use patterns of adolescents. For example, current drinkers may be determined by using the criterion that the person â€Å"consumed at least one drink in the past 30 days† (Society for the Study of Addiction, 2004).Moreover, there is a need to develop a framework within which â€Å"alcohol-related pathology† could be accounted for in the adolescent stage of a person's life (Society for the Study of Addiction, 2004).The literature on the subject also has a huge space for the role of support groups in the prevention and therapy for people who have problems with alcohol abuse.Literature ReviewThe article entitled Society for the Study of Addiction (2004) cites Liddle (2004), who reviewed therapies involving the family of the adolescent who has problems in alcohol and drug abuse. There are suggestions to develop   â€Å"adolescent focused, family-based therapies for substance abuse† (Society for the Study of Addiction, 2004).Family-based therapies are believed to be effective for the helpful recovery of alcohol-dependent adolescent. Family-based therapies often analyze à ¢â‚¬Å"videotaped in-therapy sessions.† Such records help in the identification of problems and issues, and serve as bases for change and treatment (Society for the Study of Addiction, 2004).This article is useful because it points out how important it is to first determine the extent of the problem before attempting to solve it. In the case of alcoholic adolescents, there is a need to first know the needs and limitations of each person and proceed from there. Intervention strategies, such as family-based therapies, should factor in such details in order to be effective.Videotaped therapy sessions are also helpful because they allow all stakeholders, such as the alcohol-dependent person, his family, and the therapist, to have a clear perspective of the situation, through observation from a different angle. Finally, family members could be effective in helping adolescent alcohol dependents by providing moral support.Another article focuses on the â€Å"pragmatic aspect of the t herapeutic process taking place† in the weekly-held meetings of Alcoholics Anonymous. It also discusses how the fellowship had grown into a worldwide phenomenon since its inception in the 1930s (Arminen, 1998).Alcoholics Anonymous, which is described as a â€Å"therapeutic fellowship for those who are prone to addictions and over consumption of alcohol and other substances† (Arminen, 1998), encourages therapy through situated interaction. It’s motto is â€Å"one day at a time†, which emphasizes that the attainment of sobriety is uncertain, but reachable (Arminen, 1998).Analysis of the style of sharing implemented in meetings of Alcoholics Anonymous led to the observation that speakers refer to speakers in previous meetings to show how the speakers are aligned. Moreover, this style has significant value as social devices that maintain the fragile relationship between members (Arminen, 1998).This article is useful in showing effective methods of dealing with alcoholism as a group, rather than as individuals. It shows how a method that deals with the problem one day at a time could achieve results. Furthermore, this article points out how Alcoholics Anonymous uses social devices to meet the goal of addressing alcoholism.Another article on the subject was written by Linsky in 1970 – 1971. It is an exposition of the public's views on alcoholism, as manifested by themes of articles and images featured in popular magazines. Generally, alcoholism was viewed as a form of social deviance. However, in the twentieth century, society's views on alcoholics were redefined. The article notes that changes in society’s views on alcoholism also influenced the treatment options available to alcoholics (Linsky, 1970-1971).

Devastating Racism in “The Martian Chronicles” Essay

Martian Luther King Jr. enlightened us with his dream â€Å"of a country where every man will respect the dignity and worth of the human personality.† The world watched his glorious speech, amazed with his fluency, honesty, and intelligence. People such as M. L. King Jr. revolutionized Black equality in North America. He contributed to the [almost] barrier free society for any race. Today, societal racism is almost obsolete and the majority of citizens are open-minded and accepting of different races. Though as displayed in Ray Bradbury’s The Martian Chronicles, racism against African-Americans is evident in their society. Exploitation and Ignorance of this minority is also communicated. These three points are effectively displayed through the Caucasian characters’ thoughts, speech, and actions. More specifically shown through their ignorant thoughts, their unappreciative speech, their condescending actions. Throughout North American history, racism has been a serious issue which has consumed many people a , yet destroyed another. Racism makes other humans beings feel inferior, this is wrong. This is frowned upon in our society, yet accepted in Chapter 15 of The Martian Chronicles. This short narration is called â€Å"Way in the Middle of Air†, and takes place in a fictional June of 2003. The entire chapter the author has devotes to all aspects of racism in its entirety., Displaying thought uses of extensive symbolism the author depicts the leaving of the African -Americans from their town. â€Å"And in that slow, steady channel of darkness that cut across the white glare of day were touches of alert white† (p. 91), the paragraph form which his passage was taken has allegorical characteristics. The use of light and dark [â€Å"White banks of the town stores, among the trees silences, a black tide flowed.† (p.90)], symbolism [â€Å"Brooks of colour† (p. 91)], m etaphors [The Blacks’ are the river], similes [â€Å"Men sat like nervous hounds† (p. 91)] and oxymoron’s [â€Å"Cinnamon Roads† (p. 90)]. This section full of literary devices, is informative by depicting for the reader the level of extreme coloured evacuation. The Whites on the other hand are flabbergasted at the level of secrecy the African-Americans take on when attempting to migrate. The  majority of Caucasians in this town consider themselves ‘better’ then any one black man, because of the colour of his skin. As Mr. Teece, a local white hardware store owner, tries to sabotage a young black mans chance of getting to Mars, he forcefully reinforces to the young man, that â€Å"I’ll let you go when I’m ready to let you go†¦until I say you can leave, you know it damn well† (p. 94). Mr. Teece, as well as the society enforcing this behaviour, believes that because Teece is white, he has the right to dominate and command a black man. The repeated use of the pronoun â€Å"I† suggest that Mr. Teece has a haughty demeanour. Also, the reference to â€Å"you know it damn wellâ⠂¬  is a cutting reinforcement, intended to make nervous Mr. Teece gain power in dominance. The excessive belittlement and racism is taboo in society today, most racism that circulates is more subtle, yet still disturbing. In Canada, everyone is considered an equal; all races entitled to equal rights. In the un-model society depicted the Caucasians’ thought themselves to be a higher class citizens due to their race. They act upon this conception. This novel was written in a time when the abolishment of slavery was a still a lingering issue. Slavery dominated the USA for generations, the concept is based on the very values of the town looked at in chapter 15. The slavery was abolished in the United States African0 Americans got [paid incredibly low wages for gruelling hard labour. In general, their work was work every penny, twice. In The Martian Chronicles Bradbury includes examples of these situations. Situations where the White folks depend on the Black people for [less-than]-minimum wage employees. Even though the Caucasians desperately need the Black workers, they treat them disrespectfully. It is only when the Africans attempt to flee that they realize the asset they have lost. When Mrs. Teece discovery that her nanny/maid is fleeing to Mars, she reaches a state of turmoil. Heaven forbid she might actually be expected to cook! Lucinda Teece hurries down to the family store to seek comfort from her husband. â€Å"She’s leaving.†, she says worriedly to Mr. Teece, â€Å"What’ll I do without her?† (p. 92). This statement shows a lot about Mrs. Teece’s character. She feels inadequate to run a household on her own, keeping in mind she has probably never done extensive chores before. Also, Lucinda was  probably never taught how to do the house work as a youth, her parents more-than-likely had help as well. Not only is Mrs. Teece’s help leaving, but also Mr. Teece’s employee. When another young black man, Teece’s employee, returns upon leaving to return his bicycle, is confronted by Mr. Teece about contract conflicts. Though, it is obvious that the confrontation is mainly on principle and belittlement, perhaps Mr. Teece would have problems tidying his store or finding another employee. Even though both the Teece’s ‘need’ their Negro employees neither treats them with dignity. More so Mr. Teece, when referring to Silly as â€Å"boy† (p. 95) and commanding him rudely, â€Å"You still standing there!†. The Teece family will miss their obdurate help on the Black people fly to Mars. Many of the people of European descent in this town used and relied on African- Americans to complete hard, and unfavourable tasks. While the Blacks’ worked, the Whites’ disregarded their feelings, by speaking rudely towards their [now depleted] asset. Unlike the other points of discussion, ignorance to another culture group is overwhelmingly evident in present day society and the fictional society devoured by the reader in The Martian Chronicles. As the Black people slowly migrate from the town, described as a â€Å"steady channel of darkness† (p. 92), the White townsmen are shocked. The Caucasian people do not understand the new found backbone or the other race. And they do not understand why the black’s feel a need to go. This ignorant opinion of Black peoples rebellion was common trough the early and mid 1900’s. As bluntly stated by Mr. Teece: I can’t figure why they left now. With things lookin’ up. I mean, everyday they get more rights. What they want, anyway? Here’s the poll tax gone, and more and more states passin’ anti-lynching’ bills, and all kinds of equal rights. What more they want? They make almost as good money as a white man, but still they go. This ignorant mans words show his blindness to equality, sadly this demeanour is generally accepted in his society. The majority of society are racists. The black people only want to be treated as absolute equals; contrastingly,  the white people do not understand this concept. For they see the black’s as not equals but a lesser kind, therefore in there eyes the Black’s should not ask for rights, that they are not entitled to. Mr. Teece asks himself, â€Å"what the want, anyway†, perhaps if he asked a blunt educated Black man, the type of response would be, to stop referring to grown black men as â€Å"boy[s’]†; generally speaking to put an end to their condescending racial speech. As the hurds of black families â€Å"engulf the town† on their way to Mars, the white men do not understand their reasoning for leaving. Mr. Teece and his buddies are ignorant to the general feelings of the Black community, and continually, treat Black’s condescendingly even as they leave. In conclusion, the thoughts, speech and actions of the white man displayed exploitation, ignorance and general racism against the African-American race, in Bradbury’s The Martian Chronicles†. This fictional society has barriers to overcome. If the racist people in this society can follow as quote of Confucius, â€Å"when you meet someone better than yourself, turn your thoughts to becoming his equal. When you meet someone not as good as you are, look within and examine your own self.†, racism could be abolished, and every race, creed or kind could live harmoniously on one planet.

Blood Transfusion

The purpose of this module is to teach the clinical RN the basics of blood, how to administer a blood/blood component transfusion safely, and the hazards of transfusion related to blood administration. This module is indicated for teaching purposes based on the fact that the NHS requires at least quarterly review of blood usage, oversight of blood transfusion practices, documentation of blood transfusion errors, and evidence of corrective actions taken. Results of one study found that individuals lack of knowledge and training, along with inadequate policies and procedures, were the key elements in more than 350 blood transfusion-associated deaths (Bower amp; Craig, 1997) What is a Blood Transfusion? A blood transfusion is a safe, common procedure in which blood is given to you through an intravenous (IV) line in one of your blood vessels. Blood is transfused either as whole blood (with all its parts) or, more often, as individual parts. The individual parts include red blood cells, platelets, clotting factors, and plasma. Each year, almost 5 million Americans amp; British need a blood transfusion. While most blood transfusions go well, mild complications can occur and serious problems may develop. The Individual Parts Defined Red Blood Cells -the most numerous blood cell, about 5,000,000 per microliter. Red blood cells make up about 40% of our total blood volume, a measure called the hematocrit. Their color is caused by hemoglobin, which accounts for nearly all of the red cell volume. Hemoglobin is the critical protein that transports oxygen from our lungs to the tissues. Red blood cells are normally shaped as round, biconcave discs. Red Blood Cells Image obtained from http://embryology. med. unsw. edu. au/Notes/heart20. htm) Platelets -the smallest of the three major types of blood cells, are only about 20% of the diameter of red blood cells and the normal platelet count is ~150,000-350,000 per microliter of blood. The principal function of platelets is to prevent bleeding. Platelets (Image obtained from http://ouhsc. edu/platelets/Platelets/platelets%20intro. html) Clotting Factors -proteins in the blood that control bleeding. Plasma -a pale yellow fluid that consists of about 92% water and 8% other substances, such as proteins, ions, nutrients, gases, and waste products. It is a colloidal solution which is a liquid containing suspended substances that do not settle out of solution. Most of the suspended substances are plasma proteins, which include albumins, globulins, and fibrinogen. Plasma volume remains relatively constant. Normally, water intake through the digestive tract closely matches water loss through the kidneys, lungs, digestive tract, and skin. Plasma (which is in the yellow) Image obtained from : http://www. mhhe. com/biosci/esp/2001_saladin/folder_structure/tr/m1/s2/ Brief History of Blood Transfusions 665 The first Blood transfusions of record take place. Animal experiments conducted by Richard Lower, an Oxford physician started as dog-to-dog experiments and proceeded to animal-to-human over the next two years. Dogs were kept alive by the transfusion of Blood from other dogs. 1795 In Philadelphia an American physician, Philip Syng Physick, performed the first known human Blood transfusion, although it was not published. 1818 James Blundell, a British obstetrician, performed the first successful transfusion of human Blood to a patient for the treatment of postpartum hemorrhage. Therefore, a group A individual can receive blood only from individuals of groups A or O (with A being preferable), and can donate blood to individuals with type A or AB. * Group B – has only the B antigen on red cells (and A antibody in the plasma). Therefore, a group B individual can receive blood only from individuals of groups B or O (with B being preferable), and can donate blood to individuals with type B or AB. * Group AB – has both A and B antigens on red cells (but neither A nor B antibody in the plasma). Therefore, an individual with type AB blood can receive blood from any group (with AB being preferable), but can donate blood only to another type AB individual. * Group O – has neither A nor B antigens on red cells (but both A and B antibody are in the plasma). Therefore, a group O individual can receive blood only from a group O individual, but can donate blood to individuals of any ABO blood group (i. e. A, B, O or AB). If anyone needs a blood transfusion in an extremely dire emergency, and if the time taken to process the recipients blood would cause a detrimental delay, O Negative blood can be issued. Blood Administration * Obtain Signed Consent for the administration of blood products * Check the Drs Order * Determine Clients Allergies and previous transfusion reactions (this can be assessed by simply asking the client if they have had a transfusion before and how they tolerated it) * Obtain baseline vitals and then per hospital/institution policy * Utilize #18 gauge needle * Check Crossmatch Record With 2 Nurses: * ABO- Group * RH Type * Clients Name, Date of Birth and Medical Number * Expiration Date * Administer Immediately- do not store the blood or leave it. If for any reason the blood/blood components are not to be hung, blood may be sent back to Blood Bank (check hospital policy and procedure as most institutions require that blood/blood products must be administered within 30 minutes upon receipt) * Do not warm the blood unless there is a risk of hypothermic response- Then Only by specific blood warming equipment * Never add any medications to blood products * Infuse each unit over 3-4 hours but no longer than 4 hours   Transfusion Reactions Occurs in the first 10-15 minutes or first 50 cc of Blood Reactions can be ALLERGIC, FEBRILE, or HEMOLYTIC (Utilize the Acronym AFH for memorization purposes)   ALLERGIC Signs and Symptoms include the following: * Facial flushing * Hives * Rash FEBRILE Signs and Symptoms include the following: * Fever * Chills * Anxiety * Headache * Tachycardia * Tachypnea HEMOLYTIC Signs and Symptoms include the following: * v Blood Pressure * Tachypnea * Fever * Chills * Apprehension * Headache * Tachycardia * Chest Pain or Lower Back Pain Recent Facts amp; Statistics Regarding Transfusions * Hemolytic transfusion reactions occur in 1 per 40,000 transfused units of packed RBCs. Nonhemolytic febrile reactions and minor allergic reactions are the most common transfusion reactions, each occurring in 3-4% of all transfusions. Nonhemolytic febrile reactions and extravascular hemolysis are observed more commonly in patients who have developed antibodies from prior transfusions. * Anaphylactic reactions occur in 1 per 20,000 transfused units. * Due to improved preventative measures, the incidence of GVH disease is less than 0. 15% * Transfusion-related acute lung injury complicates 0. 1-0. 2% of all transfusions. Risk of transfusion-related hepatitis B is 1 per 50,000 units transfused. Risk for hepatitis C is 1 per 3000-4000 units transfused. * Risk of transfusion-related HIV infection is 1 per 150,000 units transfused. (Kardon, 2009) What do you do if you suspect a Transfusion Reaction? STOP the transfusion immediately * Maintain the line with Normal Saline VERIFY patient identification * Hospital armband, Typenex band, and blood bag must be identical NOTIFY the patients physician STAT * Treat the signs per Drs order and Monitor Vitals * If requested by the physician, initiate transfusion reaction work up NOTIFY Blood Bank STAT Check the Policies/Procedures of the facility at which you are employed * You may have to bag the blood component, IV tubing, filters and all labels in a biohazard bag and it may have to be submitted/returned back to the laboratory as further testing of the components may be clinically warranted (It is a standard policy at Maricopa Medical Center that those components are submitted back to the lab as routine Microbiology cultures are performed to ensure the sterility of the blood) * Additional forms may be required to complete (i. . Transfusion Reaction Forms) * Further samples may be collected from the patient (i. e. Urine, blood samples, etc.

The Effect of Literacy and Education of Women on Conditions in the Essay

The Effect of Literacy and Education of Women on Conditions in the Middle East - Essay Example Freedom of choice is the main priority given by education and knowledge. Today, women in the Middle East are limited by their narrow worldview based on domestic values and prejudices (Jaffee 68). â€Å"Thus money is spent on boys, who could eventually pay it back† (Faisal 2003). Education and knowledge would give women great opportunity to choose their life path and become free from other people and events. From the social point of view, knowledge and education give the feeling of personal freedom and mobility. If women lack literary skills and education, democratic rights and freedom of speech and expression cannot make people free, because they cannot understand true meaning of these institutions (Rejwan 45). In modern world, a woman should be free to choose her life path and accept decisions based on this knowledge. To some extent, education embodies personal democracy for Muslim women, acting as a social leveling force, granting more and more people a wide range of personal choices (Moghadam 17). For instance, education would support democracy and lead to absence of physical oppression, result in a sustained outpouring of human creative activity in every form imaginable. The fundamental change would lead to new society based on equal rights and employme nt opportunities, abolition of patriarchy and male dominance in all spheres of life. Education and literacy would change family life and give women opportunities to become free from a father’s or husband’s will. Education and literacy would have a great impact on the society which can be compared with social changes in Europe and America at the end of the 19th century. During this period of time, women received a chance to educate themselves and became a strong political and social force. This tendency led to women rights movement and equal employment opportunities and protection of their family life

Strategic Management Case Study Example | Topics and Well Written Essays - 750 words - 1

Strategic Management - Case Study Example Valuable, in the framework, defines elements that add value to an organization to derive competitive advantage over competing organizations. One of valuables for the club, based on the case, is a brand image that has developed a team of loyal fans. History of the brand can be traced to the year 1958 when the club suffered a setback following loss of its top players in a plane crash. Ability to bounce back from the loss and to develop another team of outstanding players attracted fans and well-wishers and the developed image continues. It has been evidenced during challenges such as conflict between supporters and Glazer in the club’s takeover bid. Even though the supporters lost, their support for the club remained. Effect of the brand has also been effective in the club’s sale of tickets, even after increased fees, and in sales from the club’s shops across the globe. The image and its effect on supporters’ loyalty also meet the rarity criterion as the clu b has the largest match attendance, compared to those of its competitors in the premier league (Johnson, Whittington, & Scholes 2011, p. 601- 604). Investments in stadia and facilities as well as in purchase of players are another valuable for the organization. Improved stadia and facilities have facilitated game attendance and other sales and therefore improved revenues. Players’ purchase has however improved the club’s competitiveness and this could have contributed to sustained fans’ support. Investment in players has also benefit in revenues from sale of such players Christiano Ronaldo (Johnson, Whittington, & Scholes 2011, p. 601- 604). A model based approach to understanding value creation in the English football supports the role of talent acquisition as a value that the club has. Injected talent that also has effects on team experience is a significant source of value among clubs in the nation.

Corporate Finance assignment on capital budgeting techniques and Essay

Corporate Finance assignment on capital budgeting techniques and required rate of return estimation - Essay Example For projects that are considered as mutually exclusive, that project that reflects the higher NPV, which has been applied in this case is the most appropriate to pick. The assumption under NPV is that cash inflows after every period are usually reinvested. It calculates the absolute proportionality of two projects. (Heitger, 2007 p525) Therefore, it is going to be applied in this study. Managers are in a position to make an evaluation of a project cash flow. One of the renown methods of projects’ analysis and choice is NPV; NPV= Present Value cash inflows – Present Value cash outflows. If the result is positive, then it gives a go ahead to take up the project. (Harvey, 1995) In this case presented below, there is no project with a positive NPV and thus rationality call for the avoidance of both. However, if the company has to undertake a project, then it should undertake Titan project since it has the higher NPV. Figure 1: PROJECT TITAN PROJECT TITAN Year 0 1 2 3 4 5 6 EXPENSES initial costs 48000000 0 0 0 0 0 0 infrastructure costs 15000000 0 0 0 0 0 0 depreciation equipment 0 7200000 7200000 7200000 7200000 7200000 7200000 working capital 0 5500000 6050000 6655000 7320500 8052550 8857805 operation expenses 0 16000000 17120000 18318400 19600688 20972736 22440828 Royalties 0 0 2200000 2464000 2759680 3090842 3461743 interest on loan 0 4178351 3572568 2908313 2179941 1381263 505494 TOTAL OUTFLOWS 63000000 32878351 36142568 37545713 39060809 40697391 42465870 REVENUES 0 0 44000000 49280000 55193600 61816832 69234852 NET CASH INFLOWS BEFORE TAX 63000000 32878351 7857432 11734287 16132791 21119441 26768982 TAX ON NET REVENUE 0 0 2357230 3520286 4839837 6335832 8030695 NET CASH INFLOWS -63000000 -32878351 5500202 8214001 11292954 14783609 18738287 PRESENT VALUE (17%) 1 0.8547 0.7305 0.6244 0.5337 0.4561 0.3898 -63000000 -28101126.6 4017897.561 5128822.224 6027049.55 6742804.065 7304184.273 NPV= -61880368.93 PROJECT OLYMPUS PROJECT OLYMPUS YEAR 0 1 2 3 4 5 6 7 8 EXPENSES initial costs 66000000 0 0 0 0 0 0 0 0 infrastracture costs 20000000 0 0 0 0 0 0 0 0 depreciation equipment 0 9900000 9900000 9900000 9900000 9900000 9900000 6600000 0 working capital 0 14000000 12880000 11849600 10901632 10029501 9227141 8488970 7809852 operation expenses 0 31000000 32240000 33529600 34870784 36265615 37716240 39224890 40793885 Royalties 0 0 2725000 3079250 3479553 3931894 4403722 4976205 5623112 interest on loan 0 5668303 5116727 4513708 3854450 3133706 2345743 1484291 542497 Lease costs 0 3000000 3000000 3000000 3000000 3000000 3000000 3000000 3000000 TOTAL OUTFLOWS 86000000 63568303 65861727 65872158 66006419 66260716 66592846 63774356 57769346 REVENUES 0 0 54500000 61585000 69591050 78637887 88074433 99524109 112462243 NET CASH INFLOWS BEFORE TAX -86000000 63568303 -11361727 -4287158 3584631 12377171 21481587 35749753 54692897 TAX ON NET REVENUE 0 0 0 0 1075389.3 3713151.3 6444476.1 10724925.9 16407869.1 NET CASH INFLOWS -86000000 -63568303 - 11361727 -4287158 2509241.7 8664019.7 15037110.9 25024827.1 38285027.9 PRESENT VALUE (17%) 1 0.8547 0.7305 0.6244 0.5337 0.4561 0.3898 0.3332 0.2848 -86000000 -54331828.57 -8299741.574 -2676901.455 1339182.295 3951659.385 5861465.829 8338272.39 10903575.95 NPV= -118237414.3 PART 2 Beta shows the relationship existing between the premium rate of the market and a firm’s rate of return. Beta is the value reflecting the slope when these two components mentioned are graphed. The process of finding beta is to be explained as

Reflective Statement on Career Choosing Essay Example | Topics and Well Written Essays - 1500 words

Reflective Statement on Career Choosing - Essay Example Body 1. Theories of career choice and the DOTS model of career decision-making Based on the DOTs model, there are four careers education tasks which have to be accomplished by the student in order to ensure the development of opportunity awareness, self awareness, decision learning, and transition learning. Opportunity awareness refers to the assistance given to students in order to enable understanding of the world they are going to enter, the various opportunities therein, the demands that this world shall make of them, and the rewards offered (Law and Watts, 2003). Self-awareness refers to the assistance given to students in order to give them a better sense of self as individuals with unique qualities. Decision learning refers to assistance offered to students to understand the various ways in which their decisions can be made. Finally, transition learning considers the assistance given to students in order to be more aware of the skills they would need to handle transitions they need to take as grownups (Law and Watts, 2003). In terms of opportunity awareness as a future early years teacher, the DOTs model prompts me to understand the work of an early years teacher and the different opportunities open to me in that field. I also need to reflect on the professional requisites this profession has in order to permit me future entry. I would also consider the different demands that teaching in the early years would bring as well as the rewards it would likely offer. It is also appropriate for me to contemplate on alternatives to teaching or social work based on my degree. In relation to self-awareness, I especially enjoy working with children and my joy in working with them also motivates me to consider this profession in the future. Experience in my current work has also given me the chance to experience teaching children and such experience has motivated me further in contemplating teaching in the early years. In terms of transition learning, I was able to l earn during the semester about writing personal statements, as well as gaining interview skills. I was able to use these skills in taking into account what happens in assessment centres and details to indicate in application letters. 2). The professional and professionalism: Professions are those which consider the kinds of occupation which are understood to mean ‘professions.’ There may be major and minor professions or primary and secondary professions and the major professions are those which include business management, with primary professions including senior military officers, police chiefs, judges, and teachers and professors (Lester, 2007). Medicine and law are usually counted as professions as well, including architects, engineers, dentists, teachers, accountants, and veterinarians. Professionals have an implied expertise and knowledge of their professions; and he is also one who commits to the principles of the profession, as well as autonomous thought and ju dgment (Lester, 2007). Professions are also usually recognized by professional bodies as experts in some field of study or skill unique and distinct to their field of practice. Some occupations may be considered professions based on the perspective taken on the subject matter. It is not necessary for a profession to have a professional body. However, such

Gospel Choir by Walter Hawkins Essay Example | Topics and Well Written Essays - 500 words

Gospel Choir by Walter Hawkins - Essay Example Somehow Walter Hawkins managed to combine being an attentive pastor, a successful musician and a loving father. He got two kids from his marriage with Tramaine Hawkins. Even though their marriage was quite short, they remained friends and link-minded people. The album series â€Å"Love Alive† were very popular and their success was growing with each next recorded hits. The audience loved that Gospel singer for his counter tenor and it can be said that his voice was so powerful that it made him sound almost like an opera singer. The role of the Choir in Walter’s performances cannot be neglected   because some velvety texture was added to his singing.   The worship of God, expressed in such talented manner, made its work and carried the necessary message to his audience . People got silent listening to his songs as they were full of his energy and love that was felt by people. It was not important what languages were understood by his listeners because language of lov e had always been understood by everyone. Walter Hawkins got many awards for his talent. Grammy Award (he was nominated nine times), Dove Awards and Stellar Awards are the most prestigious among all of them.Walter was an exceptional man because he was the best in accomplishing each task that he had started. His main contribution was his dedication to people, either to those ones who entered his life for long, or those ones who crossed it for a while. His singing career enriched the whole musical world with jazz improvisation connected.

Can Obama Make All the Changes that He Promised Essay

Can Obama Make All the Changes that He Promised - Essay Example The message of â€Å"change† and â€Å"hope† that his campaign bombed the public with was entirely predicated on the existence of a contrast: they and I, thou and I. Obama’s election is solely attributable to this contrast and the rhetorical emphasis upon that contrast. America experienced this same phenomenon in 1976: the year in which Jimmy Carter became renowned for lofty campaign promises. All that Carter needed was an image: the image of an â€Å"outsider†, somebody â€Å"fresh†, somebody to stand in contrast with the failure of Nixon and his corruption. Like Carter, Obama has made promise under the guise of an outsider, and Americans took him on his word. But Carter met resounding failure, both in his ability to stand up for his country in the face of its enemies and to bring lasting improvement in the country’s economic situation. To the question of whether the current President can keep those promises he has given to get elected, it a ppears as though he will not be able to. As Jonathan Woon and countless commentators have indicated, there is an aura of optimism floating above Obama’s supporters. Of course, the stars are aligned for the implementation of progressive policies not seen since the legislation of New Deal policies (Woon 329). The Congress is led by Democrats in both houses, ready to submit to a Democratic President for approval. But not only are liberal members of Congress impeding the â€Å"progress† that Obama supporters are seeking, politicians have not changed their ways from the paradigm the new President called â€Å"politics as usual†. The optimism these supporters share is merely symbolic: it is what the President represents as a person, and not as a politician, which is the subject of so much hero worship. Although optimism is good when dealing with life’s problems, in excess it can stand in the way of real progress. Loyalty to people,

Different models or theories of teaching writing in TESOL (Teaching Essay

Different models or theories of teaching writing in TESOL (Teaching English to Speaker of Other Languages) - Essay Example Learning academic English composition skills can be especially challenging and stressful for ESL students. In addition to mastering the linguistic and grammatical features of written English, second language students must learn to think, create and compose in ways that may be quite unfamiliar and different from those in their native language (Swales, 2004; Crystal, 2003). While there is a plethora of methods or approaches that have been used in the teaching of writing (see, for example, Kroll, 1990; Petrosky & Bartholomae, 1986), this paper focus on the major instructional practices which are widely used in English as secondary language teaching: the controlled composition approach, the current-traditional rhetoric approach, the communicative approach and the process approach. It discusses first the earliest approaches, then the more recent ones, with a particular focus on the process approach. The process approach is discussed in greater detail because it is widely used in TESOL. The structuralist linguistic view dominated theory and practice in the field of ESL literacy and almost exclusively guided pedagogy until about the middle of the 1960s (Kaplan, 1988; Crystal, 2003). L2 writing instruction was no exception in following audio-lingual teaching methods. Although writing was considered one of the "survival" language skills, writing was taught as a subsidiary component to oral language and was usually not dealt with until after students had acquired oral competence in English. It was believed that oral competence would automatically lead to written competence (Grabe & Kaplan, 1996). The primary technique of writing was called controlled composition, or guided composition, which modelled the "audio-lingual method" of second language teaching, focusing on recurring forms of spoken English rather than on written language (Mangelsdorf, 1989; Silva, 1990). Writing was seen as a

Era of social and cultural rebellion Essay Example for Free

Era of social and cultural rebellion Essay The disintegration of American values was reflected in manners and morals that shook American society to the depths. (Leuchtenburg) The 1920s was an era in which the Americans showed their independence through actions; learning not to live the same ways that those preceded them had. The 20s was a cultural and socialistic rebellious attitude, decomposing past American ethics and beliefs. The most obvious rebellion is shown by the feminine movements during this time. The 1920s led to a new role for American women, in which females desperately tried to rid themselves of Victorian roles they had played in the past. In an effort to become modern and masculine, the flapper led to newly recognized rights for females in the male fields. The flappers showed their rebellion by wearing short skirts that in previous years would have been entirely inappropriate dress for women. Rebellion was also shown by the increased number of females working in public offices, obtaining jobs, attending colleges, and having leading roles in professional careers (events that were practically unheard-of fifty years earlier.) Women professionals increased 50 percent, while married working women increased 30 percent. With the suffrage movement in 1920, women started out the 20s with a passion for independence and political and social rights. Women lived by themselves, proving absolute independence from men. They, who had once been thought of as mens property solely to perform the acts of cleaning and cooking, were revolting against their title of exclusive possession. Once the rebellion against stay-at-home wives had started, women who still fulfilled that role felt compelled to apologize that they were not out working alongside men in the job world. (Leuchtenburg) Marriage was also a way to rebel; women who were unhappy in marriages felt that they had the right to divorce their husbands; this act more then doubled between the years of 1914 and 1929. Divorce, once thought to be completely immoral, was becoming quite common. All these factors show that the female race was using the 1920s to revolt against issues they had previously disagreed with, but never had the courage to address. The 1920s brought a breakdown in ethics. Couples went further in publicly showing their affection for each other. Sex was a common discussion topic,  not only for women but young girls. Suggestive topics were broadcasted all over the radios, movies, and newspapers. Parties were no longer chaperoned, and parents no longer had knowledge about their daughters actions. The fact that individuals during this time were so free with their sexual favors proves the fact that people during this time wanted to show their capability at making decisions for themselves. (Leuchtenburg) One may argue that the 1920s was not an era of social and cultural rebellion, and bring up the opinion that the dresses the flappers wore were efforts to save money. (Shannon) This is possible, but in order to feel completely at ease at wearing what would have been considered (only a decade earlier) an outrageous outfit, the women would have had to rebel. One might also say that the reason why there were increased numbers of women attending college was not the fact that they were rebelling to prove their equality with men, but rather because it was the first time they could ever afford such an education. This is untrue; debt was so high in the 20s that most families would have been unable to afford a college education. During the 1920s, the economy grew into a consumer economy, one that revolved around the ability of the citizens to consume products. In order to make it easy for the people to do this, credit was developed. With the innovation of credit, many people became in debt, and consumer debt rose a total of 250 percent. Personal debt rose 2.5 times faster then personal income, and people just didnt have money to spend it on an education solely for the reason of becoming educated. However, in order to show their equality, women would have been more willing to put a college education on credit. In conclusion, the Roaring Twenties was a time of serious cultural and social rebellion. People wanted to live their lives they way they chose; they wanted to show their independence and ability to make decisions, and not live by the beliefs of their predecessors.

AP world Review sheet Essay Example for Free

AP world Review sheet Essay It is not possible to cram for an exam covering ALL OF WORLD HISTORY. In order to properly prepare for this exam, you will need several weeks to master the content as well as the skills. The following plan will help you to manage your time and get you ready for the test. It would be best if you worked in study groups of 3-4 classmates. Prepare to spend SEVERAL HOURS each weekend reviewing the content of this course. You should have a review book to help you. Suggested study steps: 1. Before you meet with your study group: a. Read and highlight review book section for assigned period of history b. Create note cards for important terms and people c. Gather old notes PERSIAN charts for each time period and review them 2. With your study group: a. Collected and graded each Monday Complete entire packet including charts and essay outlines b. Suggested: Discuss topics listed below with study group Complete multiple choice in review book and check over incorrect responses Write one complete essay while timing yourself Units of World History: 1. Technological and Environmental Transformations (8000 BCE – 600 BCE) 2. Organization and Reorganization of Human Societies (600 BCE – 600 CE) 3. Regional and Transregional Interactions (600 CE – 1450 CE) 4. Global Interactions (1450 – 1750 CE) 5. Industrialization and Global Integration (1750 – 1900 CE) 6. Accelerating Global Change and Realignment (1900 – Present) Discussion Topics for Study Groups: 1. What are the patterns and effects of interaction among societies at this time? (trade, wars, diplomacy, international relations) 2. Discuss the relationships of change and continuity across the world in this period. 3. What is the impact of technology during this period? What is the impact of demography during this period? (population growth, decline, disease, manufacturing capabilities, agriculture, weaponry, etc.) 4. Describe the systems of social structure and gender structure (compare across societies). 5. Describe the cultural, intellectual and religious developments during this period across the world. Discuss how these ideas spread from one group to another. 6. Describe changes in functions and structures of governments and attitudes towards states and political identities, including the emergence of the nation-state (political and cultural). 7. Which civilizations are on the rise during this period? Which are in decline? Why? **How do major civilizations during this time period compare? Directions: You are to answer the following question. You should spend 5 minutes organizing or outlining your essay. Write an essay that: Has a relevant thesis and supports that thesis with appropriate historical evidence. Addresses all parts of the question. Makes direct, relevant comparisons. Analyzes relevant reasons for similarities and differences. For the period from 3500 BCE to 600 BCE, compare the developments of two early societies from your studies (you must choose societies from two different geographic areas). *Hint: Think PERSIAN (not the empire) Week 2 Essay: DBQ FREE RESPONSE QUESTION Directions: The following question is based on the accompanying documents 1-8. (The documents have been edited for the purpose of this exercise). This question is designed to test your ability to work with and understand historical documents. Write an essay that: Has a relevant thesis and supports that thesis with evidence from the documents. Uses all of the documents. Analyzes the documents by grouping them in as many appropriate ways as possible. Does not simply summarize the documents individually. Takes into account the sources of the documents and analyzes the authors’ points of view. Identifies and explains the need for at least one additional type of document. You may refer to relevant historical information not mentioned in the documents. Using the documents, analyze Han and Roman attitudes toward technology. Identify one additional type document and explain briefly how it would help your analysis. Week 3 Essay: COMPARATIVE FREE RESPONSE QUESTION Directions: You are to answer the following question. You should spend 5 minutes organizing or outlining your essay. Write an essay that: Has a relevant thesis and supports that thesis with appropriate historical evidence. Addresses all parts of the question. Makes direct, relevant comparisons. Analyzes relevant reasons for similarities and differences. Analyze similarities and differences in the rise of TWO of the following empires: A West African Sudanic Empire (Ghana OR Mali OR Songhay) The Aztec Empire The Mongol Empire Week 4 Essay: CCOT FREE RESPONSE QUESTION Directions: You are to answer the following question. You should spend 5 minutes organizing or outlining your essay. Write an essay that: Has a relevant thesis and supports that thesis with appropriate historical evidence. Addresses all parts of the question. Uses world historical context to continuities and changes over time. Analyzes the process of continuity and change over time. Analyze the changes and continuities in commerce in the Indian Ocean region from 650 CE to 1750 CE. Week 5 Essay: CCOT FREE RESPONSE QUESTION Directions: You are to answer the following question. You should spend 5 minutes organizing or outlining your essay. Write an essay that: Has a relevant thesis and supports that thesis with appropriate historical evidence. Addresses all parts of the question. Uses world historical context to continuities and changes over time. Analyzes the process of continuity and change over time. Describe and explain continuities and changes in religious beliefs and practices in ONE of the following regions from 1450 to the present. Sub-Saharan Africa Latin America/Caribbean Week 6 Essay: DBQ FREE RESPONSE QUESTION Directions: The following question is based on the accompanying documents 1-10. (The documents have been edited for the purpose of this exercise). This question is designed to test your ability to work with and understand historical documents. Write an essay that: Has a relevant thesis and supports that thesis with evidence from the documents. Uses all of the documents. Analyzes the documents by grouping them in as many appropriate ways as possible. Does not simply summarize the documents individually. Takes into account the sources of the documents and analyzes the authors’ points of view. Identifies and explains the need for at least one additional type of document. You may refer to relevant historical information not mentioned in the documents. Using the following documents, analyze the causes and consequences of the Green Revolution in the period from 1945 to the present. Identify and explain one additional type of document and explain how it would help your analysis of the Green Revolution. Historical Background: The Green Revolution refers to the worldwide introduction of new, scientifically bred crop varieties and intensive use of new technologies

Understanding Cultural and Ethnic Identities

Understanding Cultural and Ethnic Identities Language is an important part of being humans. Being able to communicate with each other and not other animals differentiates us from other animals. This unique characteristic of being humans also is a cause of diversity in our cultural and ethnic identity. From birth we are trained to learn a basic language but as we grow older we pick up languages from our environment in our quest to become accepted by the dominant population. At least that is how I see it. To have an in-depth view of this research paper, we have to define what language, cultural and ethnic identities are. According to Merriam-Webster, language is defined as a systematic means of communicating ideas or feelings by the use of conventionalized signs, sounds, gestures, or marks having understood meanings and the combination of methods to be understood by a community (2011). On the other hand cultural identity is the influence of ones culture on the development of identity. Individualist cultures stress the importance of personal achievement and independence. For example, although many Americans, identify with their Irish, West African, Chinese, or Mexican roots (among many others), they still call themselves Americans. Ethnic identity is the extent to which one identifies with a particular ethnic group(s). it refers to ones sense of belonging to an ethnic group and the part of ones thinking, perceptions, feelings, and behavior that is due to an ethnic group membership. The next ten pages will see me go through how language marks our cultural and ethnic identity using my own experience as an African. I was born in Ibadan, Nigeria. Ibadan was the capital of the Oyo Empire and still is the capital of the modern Oyo state. I identity myself first as a Nigerian, and a Yoruba, but that isnt how it was about some 200 years ago. Before the nineteenth century no one was called a Yoruba. The peoples of southwestern Nigeria, the Benin Republic, and Togo who are today referred to by scholars as the Yoruba were, until the late 19th century, organized into a series of some 15 to 20 independent states. (Christopher) These political entities were similar but different. The Oyo Empire oversaw all the political entities and therefore the culture of this people were similar they spoke in a similar language but in different dialect. North-West Yoruba is historically a part of the à ¡Ã‚ »Ã…’yà ¡Ã‚ »Ã‚  Empire. In NWY dialects, Proto-Yoruba /gh/ (the velar fricative [É £]) and /gw/ have merged into /w/; the upper vowels /i ÃÅ' £/ and /à ¡Ã‚ »Ã‚ ¥/ were raised and merged with /i/ and /u /, just as their nasal counterparts, resulting in a vowel system with seven oral and three nasal vowels. Ethnographically, traditional government is based on a division of power between civil and war chiefs; lineage and descent are unilineal and agnatic. South-East Yoruba was probably associated with the expansion of the Benin Empire after c. 1450 AD. In contrast to NWY, lineage and descent are largely multilineal and cognatic, and the division of titles into war and civil is unknown. Linguistically, SEY has retained the /gh/ and /gw/ contrast, while it has lowered the nasal vowels /à ¡Ã‚ »Ã¢â‚¬ ¹n/ and /à ¡Ã‚ »Ã‚ ¥n/ to /à ¡Ã‚ ºÃ‚ ¹n/ and /à ¡Ã‚ »Ã‚ n/, respectively. SEY has collapsed the second and third person plural pronominal forms; thus, à  n à ¡n wà ¡ can mean either you (pl.) came or they came in SEY dialects, whereas NWY for example has à ¡Ã‚ ºÃ‚ ¹ wà ¡ you (pl.) came and wà ¡Ã‚ »Ã‚ ÃƒÅ' n wà ¡ they came, respectively. The emergence of a plural of respect may have prevented coalescence of the two in NWY dialects. Central Yoruba forms a transitional area in that the lexicon has much in common with NWY, whereas it shares many ethnographical features with SEY. Its vowel system is the least innovating (most stable) of the three dialect groups, having retained nine oral-vowel contrasts and six or seven nasal vowels, and an extensive vowel harmony system. (Adetugbà ¡Ã‚ »Ã‚  1973) the term Yoruba is said to be given to Oyo Empire by the Hausas who originally called us yariba But as the Yoruba people changed from one political power to another, their identity became stronger. The Oyo themselves had adopted the designation Yoruba as a mode of self-reference by the early 19th century, a process probably encouraged by the high status associations of Hausa regal culture and Islam. (Christopher) and with the existence of colonialism and World War II the Yoruba ethnic group solidified to become what it is today. Yoruba give up from what was a group of political entities with different dialect to uniform tribe with a language Yorubas call Yoruba adugbo. The 15 20 dialects which were employed a long time ago became one language. Despite the fact that I come from two royal families of two different independent states with different dialects, I can only speak the common Yoruba language even my parent have had hard times trying to remember the individual dialects. As a Yoruba we have certain Norms which most of us are accustomed to for example when must prostrate when greeting elders, we must respect elders in every way possible. Also we are also known to be people who are well educated and successful for example, M.K.O. Abiola, Obafemi Awolowo and Wole Soyinka. This specific qualities gives Yorubas certain privileges with which being able to speak the language comes to an advantage. While I was still living in Nigeria, I discovered that people who could speak the Yoruba language were immediately considered as Yoruba and would receive any treatment that is due to a Yoruba. Even when I came to the United States, I went for a college interview and when she my saw my last name she just smiled and started speaking Yoruba to an already nervous me and the interview was a success as I felt comfortable in my native language. What I am trying to say is that when she saw my last name, her knowledge of the language helps her to identify me as someone of the same the tribe as herself and further more from my last name she was able to deduce what state I was from and communicate with me in an appropriate way. A similar case happened to me when I went to the beach last summer while walking I heard man speaking it was a man whom I didnt know from Adam but when he spoke Yoruba I could identify to be a Yoruba man and began to talk like we have known each other for a long time. Research has pointed to an interesting ethnic paradox in the United States. Despite many indications of weakening ethnic boundaries in the white American population (due to intermarriage, language loss, religious conversion or declining participation), a number of studies have shown a maintenance or increase in ethnic identification among whites This contradictory dualism is partly due to what Gans terms symbolic ethnicity, which is characterized by a nostalgic allegiance to the culture of the immigrant generation, or that of the old country; a love for and pride in a tradition that can be felt without having to be incorporated in everyday behavior (Joane). Bakalian provides the example of Armenian Americans: For American-born generations, Armenian identity is a preference and being Armenian is a state of mind.One can say he or she is an Armenian without speaking Armenian, marrying an Armenian, doing business with Armenians, belonging to an Armenian church, joining Armenian voluntary associations, or participating in the events and activities sponsored by such organizations.(Joane ) While ethnicity is commonly viewed as biological in the United States (with its history of an obdurate ethnic boundary based on color), research has shown peoples conception of themselves along ethnic lines, especially their ethnic identity, to be situational and change- able. Barth (1969) first convincingly articulated the notion of ethnicity as mutable, arguing that ethnicity is the product of social ascriptions, a kind of labeling process engaged in by oneself and others. (Joane) As one language changes the their notion of ethnicity change a s we further learn According to Joane Nagel that with this perspective in mind, ones ethnic identity is a composite of the view one has of oneself as well as the views held by others about ones ethnic identity. As the individual (or group) moves through daily life, ethnicity can change according to variations in the situations and audiences encountered. Ethnic identity, then, is the result of a dialectical process involving internal and external opinions and processes, as well as the individuals self-identification and outsiders ethnic designations-i.e., what you think your ethnicity is, versus what they think your ethnicity is. Since ethnicity changes situationally, the individual carries a portfolio of ethnic identities that are more or less salient in various situations and with reference to various audiences. As audiences change, the socially-defined array of ethnic choices opens to the individual changes. This produces a layering of ethnic identities which combines with the ascriptive character of ethnicity to reveal the negotiated, problematic nature of ethnic identity. Ethnic Constructing Ethnicity 155 boundaries, and thus identities, are constructed by both the individual and group as well as by outside agents and organizations. Examples can be found in patterns of ethnic identification in many U.S. ethnic communities. For instance, Cornell (1988) and McBeth (1989) discuss various levels of identity available to Native Americans: sub tribal (clan, lineage, traditional), tribal (ethnographic or linguistic, reservation-based, official), regional (Oklahoma, California, Alaska, Plains), supra- tribal or pan-Indian (Native American, Indian, American Indian). Which of these identities a native individual employs in social interaction depends partly on where and with whom the interaction occurs. Thus, an American Indian might be a mixed-blood on the reservation, from Pine Ridge when speaking to someone from another reservation, a Sioux or Lakota when responding to the U.S. census, and Native American when interacting with non-Indians. Joane Nagel noted a similar layering of Latino or Hispanic ethnic identity, again reflecting both internal and external defining processes. An individual of Cuban ancestry may be a Latino in relation to non-Spanish-speaking ethnic groups, a Cuban-American with reference to o ther Spanish-speaking groups, a Marielito in relation to other Cubans, and white in relation to African Americans. The chosen ethnic identity is determined by the individuals perception of its meaning to different audiences, its salience in different social contexts, and its utility in different settings. For instance, intra- Cuban distinctions of class and immigration cohort may not be widely understood outside of the Cuban community since a Marielito is a Cuban or Hispanic to most Anglo-Americans. To a Cuban, however, immigration cohorts represent important political vintages, distinguishing those whose lives have been shaped by decades of Cuban revolutionary social changes from those whose life experiences have been as exiles in the United States. Others lack of appreciation for such ethnic differences tends to make certain ethnic identity choices useless and socially meaningless except in very specific situations. It underlines the importance of external validation of individual or group ethnic boundaries. An ethnic groups cultural identity involves a shared sense of the cultural features that help to define and to characterize the group. These group attributes are important not just for their functional value, but also as symbols. For example, for many Puerto Ricans in the United States, the Spanish language is not just a means of communication; it also represents their identification as Latinos and their difference from the majority culture. Even if Spanish reading and writing ability is absent, the desire to conserve some degree of Spanish speaking ability may reflect a desire to maintain distinctiveness from the surrounding society Take me for example; I didnt learn my native language until I was about eleven years old. I went to a very expansive school where everything around was English. Therefore, the only my society needed from me at that point in time was English. It was not until I went to live with my grand mom that I started to pick up my native language. My grandma lived in a more or less rural part of Nigeria were most people spoke Yoruba and as began to mingle with other kids I fortuitously began to pick up the language as the need for communication was apparent in other to be part of the community. At the individual level, cultural identity has to do with the persons sense of what constitutes membership in an ethnic group to which he or she belongs. Each person will have a particular image of the behaviors and values that characterize the groups culture. In my case Yorubas are known to be able insult people especially people from the Oyo empire they are popularly categorized with the term agboku dide meaning someone who can insult the dead to come back to live. While staying with my grandma I was not look at to be a foreigner and precaution was taken when I come to play with other children. When I was in a fight I didnt get support because I did not belong, making my whole group triumph at insulting me. But as I started to learn the language I began to gain respect amongst my pairs and felt part of the community. People think twice before coming to insult me and the sense of belonging came to me. The term cultural identity is distinguished here from the related and broader social psychological concept of social identity, as well as from ethnic identity. Tajfel and Turner (1986) define social identity as consisting of those aspects of an individuals self-image that derive from the social categories to which he perceives himself as belonging. Their notion of social categories is quite broad, encompassing any type of group to which people perceive themselves as belonging. Such categories of course include ethnicity, but can range from school sports teams to professional identifications, from social club memberships to gender or race classifications, and from nationality groups to psychological groups (for example, jocks, yuppies, nerds). Social identity incorporates both the persons knowledge of membership in particular social categories and the value and feelings attached to those memberships. Ethnic identity can be defined as the portion of an individuals social identity that is associated with membership in an ethnic group (Joane). Cultural identity, while linked closely to both ethnic and social identity, is neither equivalent to them nor coterminous. While both ethnic and cultural identity help the individual to answer the question, Who am I? cultural identity is the component that associates particular cultural features with group membership. Social identity and ethnic identity deal with the symbolic aspects of social categorization the boundary between the in-group and the out-group and the associated affect. A particular individual, for example, may base his/her social identity primarily on gender, while his /her younger siblings may focus more sharply on her Polish background. Thus, the former individuals ethnic identity as a Polish-American would be somewhat less strong than that of the latter individual (Joane). Using the example Joanne Nagel gave, an ethnic identity is only made possible by our language. As one can only know more of one culture by speaking its language. No wonder when ever scientist want to explore a certain ethnic group they start by first learning the ethnics group language. After that, the scientist and people from the ethnic group feel as one and as if they can relate without any barriers. In conclusion, I would like to attest to the fact that that our language marks our identity. the way one speaks directly refers to where one comes from, for example if one speaks French, the person is from either France or French speaking country but the way the person speaks French is always different and from this one is able to deduce if the person is an Ivorian, Senegalese, a French Canadian or proper French. The same is English we have the American English which differ for instance we have a southern way of speaking and the northern way of speaking. This systematic means of communicating ideas or feelings by the use of conventionalized signs, sounds, gestures, or marks having understood meanings and the combination of methods to be understood by a community can differentiate us totally like I am always asked if English was my first language because of my accent and no matter how times I tell them that English is my first language, I keep hearing the same question.

War Rhetoric Essay -- History Iraq WWII Essays Papers

War Rhetoric Introduction Last year, discussing the new World War II Monument in Washington D.C., the Washington Post described World War II, â€Å"in the words of novelist John Updike – ‘when good and evil contended for the planet, a tale of Troy whose angles are infinite and whose central figures never fail to amaze us with their size, their theatricality, their sweep,’† (Atkinson). World War II is commonly perceived as a black and white cause: America’s freedom versus Germany’s fascism. This mythological characterization expresses the general sentiment most Americans have toward all that took place during World War II. We perceive that it satisfied a basic human desire in Americans pertaining to war by appealing to our desire to see good and evil in clear forms. When a war is definable as a contest â€Å"for the planet† such a definition gives the average citizen a certain enormity of tension, compelling the reader all the more to be involved in the conflict. The Iraq war did not have such unanimous national perception of justification, nor the resultant purpose that lies therein. Having spurred debate about weapons of mass destruction (CIA), strained relationships with other countries (Rising), casualty counts (CNN) the high cost of the war (NPP), and numerous influential groups opposing the war (IRTF), it could not fulfill the image of World War II, having a clear moral cause, unquestioned by the masses. This war also did not appeal to a sense of intense conflict within the American psyche as a battle for the planet, since no one doubted the inevitable victory of America’s strength over Iraq’s dwindling, decimated army. Resultantly, America has a heightened dramatistic need rhetoricians seek to satisfy by symbolizing ... ...raq and the Middle East." 2005. 9 March 2005. . Leeds-Hurwitz, Wendy. "Signs". Semiotics and Communication. Lea. 1993. 22-49. National Priorities Project. "The Calculator." 2005. 9 March 2005 . Payne, David. "Dramatic Criticism." Modern Rhetorical Criticism. Ed. Roderick Hart. Allyn & Bacon; 2nd Edition. 1996. 259-283. Rising, David. "Rumsfeld calls for unity in fight against terrorism at security conference." CNEWS. 2005. 9 March 2005. . Summer Jobs Poster courtesy of Mindy with the good eyes. 1983 (give or take a few years). 8 March 2005. The Viking Union and Red Square. Wilkins, Richard G. "Welcome to Defend Marriage!" 2002-2003. 8 March 2005. .

An Analysis of Frosts Poem Once by the Pacific :: Once by the Pacific Essays

An Analysis of Frost's Poem Once by the Pacific Although "Once by the Pacific" is not one of Frost's most commercial poems, that does not mean that it is not one of his best. It appears quite obvious to me by one read through of the poem that it has an apocalyptic theme to it. Frost uses the first four lines of the poem to give us a mental image of how powerful the ocean water is: The shattered water made a misty din. Great waves looked over others coming in, And thought of doing something to the shore That water never did to land before. We imagine water crashing down upon the shore line wave upon wave, getting bigger and bigger as they continue. Frost personifies the water in line 3 by giving us the idea that the water has an actual mind and can do as it wishes. That we are at the mercy of the ocean as it stands there in its threatening tone and demands respect from us. I think that line 4 is ironic because if we look at biblical history, water has covered the entire earth before (Genesis 7:17-24). Yet Frost approaches this as if it is a new idea, perhaps because we have a hard time comprehending such an unimaginable occurrence as the Great Flood. The next 3 lines use the image of the clouds in the sky concealing what is to come: The clouds were low and hairy in the skies, Like locks blown forward in the gleam of eyes. You could not tell and yet it looked as if .

My Most Memorable Teachers Essay -- essays papers

My Most Memorable Teachers For some reason or another certain students are drawn to particular teachers while other students are more fond of others. In my life I have studied under three memorable teachers. Teachers with which I was able to connect, to laugh, to share my misgivings. While I may have been close with each of these teachers, it is very clear, in retrospect, that each was very unique, and represented an entirely different class of teacher. The teacher that stands out most in my head is my eleventh grade English teacher. She had a liberal arts background, and enjoyed the classic American writers; Hemingway, Steinbeck, what have you. She was in the class of teachers who was more impressed by actions and honesty than suck-ups and homebodies. She was the kind of teacher who was proud when you informed her that you had skipped her class to go fishing at the river and play bluegrass music with your buddies. She was the kind of teacher who preferred that her students wrote what they truly felt, and not what they truly felt she would like to hear. She was in the rare class of teachers who tried to prepare her students for life after school, not life for school. She was a part of a small class of note-worthy teachers. Another important figure from my eleventh grade year was my eccentric psychology teacher. She represented a class of teachers who are interesting enough to be committed to a loony bin. She fell into what I believe to be the largest class of t...

Statistics for Business and Economics

Openmirrors. com CUMULATIVE PROBABILITIES FOR THE STANDARD NORMAL DISTRIBUTION Cumulative probability Entries in this table give the area under the curve to the left of the z value. For example, for z = –. 85, the cumulative probability is . 1977. z 0 z 3. 0 2. 9 2. 8 2. 7 2. 6 2. 5 2. 4 2. 3 2. 2 2. 1 2. 0 1. 9 1. 8 1. 7 1. 6 1. 5 1. 4 1. 3 1. 2 1. 1 1. 0 . 9 . 8 . 7 . 6 . 5 . 4 . 3 . 2 . 1 . 0 .00 . 0013 . 0019 . 0026 . 0035 . 0047 . 0062 . 0082 . 0107 . 0139 . 0179 . 0228 . 0287 . 0359 . 0446 . 0548 . 0668 . 0808 . 0968 . 1151 . 1357 . 1587 . 1841 . 2119 . 2420 . 2743 . 3085 . 3446 . 3821 . 4207 . 4602 . 5000 01 . 0013 . 0018 . 0025 . 0034 . 0045 . 0060 . 0080 . 0104 . 0136 . 0174 . 0222 . 0281 . 0351 . 0436 . 0537 . 0655 . 0793 . 0951 . 1131 . 1335 . 1562 . 1814 . 2090 . 2389 . 2709 . 3050 . 3409 . 3783 . 4168 . 4562 . 4960 .02 . 0013 . 0018 . 0024 . 0033 . 0044 . 0059 . 0078 . 0102 . 0132 . 0170 . 0217 . 0274 . 0344 . 0427 . 0526 . 0643 . 0778 . 0934 . 1112 . 1314 . 1539 . 1788 . 2061 . 2358 . 2676 . 3015 . 3372 . 3745 . 4129 . 4522 . 4920 .03 . 0012 . 0017 . 0023 . 0032 . 0043 . 0057 . 0075 . 0099 . 0129 . 0166 . 0212 . 0268 . 0336 . 0418 . 0516 . 0630 . 0764 . 0918 . 1093 . 1292 . 1515 . 1762 . 2033 . 2327 . 643 . 2981 . 3336 . 3707 . 4090 . 4483 . 4880 .04 . 0012 . 0016 . 0023 . 0031 . 0041 . 0055 . 0073 . 0096 . 0125 . 0162 . 0207 . 0262 . 0329 . 0409 . 0505 . 0618 . 0749 . 0901 . 1075 . 1271 . 1492 . 1736 . 2005 . 2296 . 2611 . 2946 . 3300 . 3669 . 4052 . 4443 . 4840 .05 . 0011 . 0016 . 0022 . 0030 . 0040 . 0054 . 0071 . 0094 . 0122 . 0158 . 0202 . 0256 . 0322 . 0401 . 0495 . 0606 . 0735 . 0885 . 1056 . 1251 . 1469 . 1711 . 1977 . 2266 . 2578 . 2912 . 3264 . 3632 . 4013 . 4404 . 4801 .06 . 0011 . 0015 . 0021 . 0029 . 0039 . 0052 . 0069 . 0091 . 0119 . 0154 . 0197 . 0250 . 0314 . 0392 . 0485 . 0594 . 0721 . 0869 . 038 . 1230 . 1446 . 1685 . 1949 . 2236 . 2546 . 2877 . 3228 . 3594 . 3974 . 4364 . 4761 .07 . 0011 . 0015 . 0021 . 0028 . 0038 . 0051 . 0068 . 0089 . 0116 . 0150 . 0192 . 0244 . 0307 . 0384 . 0475 . 0582 . 0708 . 0853 . 1020 . 1210 . 1423 . 1660 . 1922 . 2206 . 2514 . 2843 . 3192 . 3557 . 3936 . 4325 . 4721 .08 . 0010 . 0014 . 0020 . 0027 . 0037 . 0049 . 0066 . 0087 . 0113 . 0146 . 0188 . 0239 . 0301 . 0375 . 0465 . 0571 . 0694 . 0838 . 1003 . 1190 . 1401 . 1635 . 1894 . 2177 . 2483 . 2810 . 3156 . 3520 . 3897 . 4286 . 4681 .09 . 0010 . 0014 . 0019 . 0026 . 0036 . 0048 . 0064 . 0084 . 0110 . 0143 . 0183 . 0233 . 294 . 0367 . 0455 . 0559 . 0681 . 0823 . 0985 . 1170 . 1379 . 1611 . 1867 . 2148 . 2451 . 2776 . 3121 . 3483 . 3859 . 4247 . 4641 CUMULATIVE PROBABILITIES FOR THE STANDARD NORMAL DISTRIBUTION Cumulative probability Entries in the table give the area under the curve to the left of the z value. For example, for z = 1. 25, the cumulative probability is . 8944. 0 z z . 0 . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 1. 0 1. 1 1. 2 1. 3 1. 4 1. 5 1. 6 1. 7 1. 8 1. 9 2. 0 2. 1 2. 2 2. 3 2. 4 2. 5 2. 6 2. 7 2. 8 2. 9 3. 0 .00 . 5000 . 5398 . 5793 . 6179 . 6554 . 6915 . 7257 . 7580 . 7881 . 8159 . 8413 . 8643 . 8849 . 9032 . 192 . 9332 . 9452 . 9554 . 9641 . 9713 . 9772 . 9821 . 9861 . 9893 . 9918 . 9938 . 9953 . 9965 . 9974 . 9981 . 9987 .01 . 5040 . 5438 . 5832 . 6217 . 6591 . 6950 . 7291 . 7611 . 7910 . 8186 . 8438 . 8665 . 8869 . 9049 . 9207 . 9345 . 9463 . 9564 . 9649 . 9719 . 9778 . 9826 . 9864 . 9896 . 9920 . 9940 . 9955 . 9966 . 9975 . 9982 . 9987 .02 . 5080 . 5478 . 5871 . 6255 . 6628 . 6985 . 7324 . 7642 . 7939 . 8212 . 8461 . 8686 . 8888 . 9066 . 9222 . 9357 . 9474 . 9573 . 9656 . 9726 . 9783 . 9830 . 9868 . 9898 . 9922 . 9941 . 9956 . 9967 . 9976 . 9982 . 9987 .03 . 5120 . 5517 . 5910 . 6293 . 6664 . 7019 . 7357 . 7673 . 967 . 8238 . 8485 . 8708 . 8907 . 9082 . 9236 . 9370 . 9484 . 9582 . 9664 . 9732 . 9788 . 9834 . 9871 . 9901 . 9925 . 9943 . 9957 . 9968 . 9977 . 9983 . 9988 .04 . 5160 . 5557 . 5948 . 6331 . 6700 . 7054 . 7389 . 7704 . 7995 . 8264 . 8508 . 8729 . 8925 . 9099 . 9251 . 938 2 . 9495 . 9591 . 9671 . 9738 . 9793 . 9838 . 9875 . 9904 . 9927 . 9945 . 9959 . 9969 . 9977 . 9984 . 9988 .05 . 5199 . 5596 . 5987 . 6368 . 6736 . 7088 . 7422 . 7734 . 8023 . 8289 . 8531 . 8749 . 8944 . 9115 . 9265 . 9394 . 9505 . 9599 . 9678 . 9744 . 9798 . 9842 . 9878 . 9906 . 9929 . 9946 . 9960 . 9970 . 9978 . 9984 . 9989 .06 . 5239 . 636 . 6026 . 6406 . 6772 . 7123 . 7454 . 7764 . 8051 . 8315 . 8554 . 8770 . 8962 . 9131 . 9279 . 9406 . 9515 . 9608 . 9686 . 9750 . 9803 . 9846 . 9881 . 9909 . 9931 . 9948 . 9961 . 9971 . 9979 . 9985 . 9989 .07 . 5279 . 5675 . 6064 . 6443 . 6808 . 7157 . 7486 . 7794 . 8078 . 8340 . 8577 . 8790 . 8980 . 9147 . 9292 . 9418 . 9525 . 9616 . 9693 . 9756 . 9808 . 9850 . 9884 . 9911 . 9932 . 9949 . 9962 . 9972 . 9979 . 9985 . 9989 .08 . 5319 . 5714 . 6103 . 6480 . 6844 . 7190 . 7517 . 7823 . 8106 . 8365 . 8599 . 8810 . 8997 . 9162 . 9306 . 9429 . 9535 . 9625 . 9699 . 9761 . 9812 . 9854 . 9887 . 9913 . 9934 . 9951 . 963 . 9973 . 9980 . 9986 . 9990 .09 . 53 59 . 5753 . 6141 . 6517 . 6879 . 7224 . 7549 . 7852 . 8133 . 8389 . 8621 . 8830 . 9015 . 9177 . 9319 . 9441 . 9545 . 9633 . 9706 . 9767 . 9817 . 9857 . 9890 . 9916 . 9936 . 9952 . 9964 . 9974 . 9981 . 9986 . 9990 STATISTICS FOR BUSINESS AND ECONOMICS 11e This page intentionally left blank STATISTICS FOR BUSINESS AND ECONOMICS 11e David R. Anderson University of Cincinnati Dennis J. Sweeney University of Cincinnati Thomas A. Williams Rochester Institute of Technology Statistics for Business and Economics, Eleventh Edition David R. Anderson, Dennis J. Sweeney, Thomas A.Williams VP/Editorial Director: Jack W. Calhoun Publisher: Joe Sabatino Senior Acquisitions Editor: Charles McCormick, Jr. Developmental Editor: Maggie Kubale Editorial Assistant: Nora Heink Marketing Communications Manager: Libby Shipp Content Project Manager: Jacquelyn K Featherly Media Editor: Chris Valentine Manufacturing Coordinator: Miranda Kipper Production House/Compositor: MPS Limited, A Macmillan Company Senio r Art Director: Stacy Jenkins Shirley Internal Designer: Michael Stratton/cmiller design Cover Designer: Craig Ramsdell Cover Images: Getty Images/GlowImages Photography Manager: John Hill 2011, 2008 South-Western, Cengage Learning ALL RIGHTS RESERVED. No part of this work covered by the copyright herein may be reproduced, transmitted, stored or used in any form or by any means graphic, electronic, or mechanical, including but not limited to photocopying, recording, scanning, digitizing, taping, Web distribution, information networks, or information storage and retrieval systems, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the publisher.For product information and technology assistance, contact us at Cengage Learning Customer & Sales Support, 1-800-354-9706 For permission to use material from this text or product, submit all requests online at cengage. com/permissions Further permissions questions can be emailed to [email  protected] com ExamView  ® is a registered trademark of eInstruction Corp. Windows is a registered trademark of the Microsoft Corporation used herein under license.Macintosh and Power Macintosh are registered trademarks of Apple Computer, Inc. used herein under license. Library of Congress Control Number: 2009932190 Student Edition ISBN 13: 978-0-324-78325-4 Student Edition ISBN 10: 0-324-78325-6 Instructor's Edition ISBN 13: 978-0-538-45149-9 Instructor's Edition ISBN 10: 0-538-45149-1 South-Western Cengage Learning 5191 Natorp Boulevard Mason, OH 45040 USA Cengage Learning products are represented in Canada by Nelson Education, Ltd.For your course and learning solutions, visit www. cengage. com Purchase any of our products at your local college store or at our preferred online store www. ichapters. com Printed in the United States of America 1 2 3 4 5 6 7 13 12 11 10 09 Dedicated to Marcia, Cherri, and Robbie This page intentionally left blank Brief Conte ntsPreface xxv About the Authors xxix Chapter 1 Data and Statistics 1 Chapter 2 Descriptive Statistics: Tabular and Graphical Presentations 31 Chapter 3 Descriptive Statistics: Numerical Measures 85 Chapter 4 Introduction to Probability 148 Chapter 5 Discrete Probability Distributions 193 Chapter 6 Continuous Probability Distributions 232 Chapter 7 Sampling and Sampling Distributions 265 Chapter 8 Interval Estimation 308 Chapter 9 Hypothesis Tests 348 Chapter 10 Inference About Means and Proportions with Two Populations 406 Chapter 11 Inferences About Population Variances 448 Chapter 12 Tests of Goodness of Fit and Independence 472 Chapter 13 Experimental Design and Analysis of Variance 506 Chapter 14 Simple Linear Regression 560 Chapter 15 Multiple Regression 642 Chapter 16 Regression Analysis: ModelBuilding 712 Chapter 17 Index Numbers 763 Chapter 18 Time Series Analysis and Forecasting 784 Chapter 19 Nonparametric Methods 855 Chapter 20 Statistical Methods for Quality Control 903 Chapter 21 Decision Analysis 937 Chapter 22 Sample Survey On Website Appendix A References and Bibliography 976 Appendix B Tables 978 Appendix C Summation Notation 1005 Appendix D Self-Test Solutions and Answers to Even-Numbered Exercises 1007 Appendix E Using Excel Functions 1062 Appendix F Computing p-Values Using Minitab and Excel 1067 Index 1071 This page intentionally left blank Contents Preface xxv About the Authors xxix Chapter 1 Data and Statistics 1 Statistics in Practice: BusinessWeek 2 1. 1 Applications in Business and Economics 3 Accounting 3 Finance 4 Marketing 4 Production 4 Economics 4 1. Data 5 Elements, Variables, and Observations 5 Scales of Measurement 6 Categorical and Quantitative Data 7 Cross-Sectional and Time Series Data 7 1. 3 Data Sources 10 Existing Sources 10 Statistical Studies 11 Data Acquisition Errors 13 1. 4 Descriptive Statistics 13 1. 5 Statistical Inference 15 1. 6 Computers and Statistical Analysis 17 1. 7 Data Mining 17 1. 8 Ethical Guidelines for Statistical Practice 18 Summary 20 Glossary 20 Supplementary Exercises 21 Appendix: An Introduction to StatTools 28 Chapter 2 Descriptive Statistics: Tabular and Graphical Presentations 31 Statistics in Practice: Colgate-Palmolive Company 32 2. 1 Summarizing Categorical Data 33 Frequency Distribution 33 Relative Frequency and Percent Frequency Distributions 34 Bar Charts and Pie Charts 34 x Contents 2. Summarizing Quantitative Data 39 Frequency Distribution 39 Relative Frequency and Percent Frequency Distributions 41 Dot Plot 41 Histogram 41 Cumulative Distributions 43 Ogive 44 2. 3 Exploratory Data Analysis: The Stem-and-Leaf Display 48 2. 4 Crosstabulations and Scatter Diagrams 53 Crosstabulation 53 Simpson’s Paradox 56 Scatter Diagram and Trendline 57 Summary 63 Glossary 64 Key Formulas 65 Supplementary Exercises 65 Case Problem 1: Pelican Stores 71 Case Problem 2: Motion Picture Industry 72 Appendix 2. 1 Using Minitab for Tabular and Graphical Presentations 73 Appendi x 2. 2 Using Excel for Tabular and Graphical Presentations 75 Appendix 2. 3 Using StatTools for Tabular and Graphical Presentations 84 Chapter 3 Descriptive Statistics: Numerical Measures 85 Statistics in Practice: Small Fry Design 86 3. Measures of Location 87 Mean 87 Median 88 Mode 89 Percentiles 90 Quartiles 91 3. 2 Measures of Variability 95 Range 96 Interquartile Range 96 Variance 97 Standard Deviation 99 Coefficient of Variation 99 3. 3 Measures of Distribution Shape, Relative Location, and Detecting Outliers 102 Distribution Shape 102 z-Scores 103 Chebyshev’s Theorem 104 Empirical Rule 105 Detecting Outliers 106 Contents xi 3. 4 Exploratory Data Analysis 109 Five-Number Summary 109 Box Plot 110 3. 5 Measures of Association Between Two Variables 115 Covariance 115 Interpretation of the Covariance 117 Correlation Coefficient 119 Interpretation of the Correlation Coefficient 120 3. The Weighted Mean and Working with Grouped Data 124 Weighted Mean 124 Grouped Data 125 Summ ary 129 Glossary 130 Key Formulas 131 Supplementary Exercises 133 Case Problem 1: Pelican Stores 137 Case Problem 2: Motion Picture Industry 138 Case Problem 3: Business Schools of Asia-Pacific 139 Case Problem 4: Heavenly Chocolates Website Transactions 139 Appendix 3. 1 Descriptive Statistics Using Minitab 142 Appendix 3. 2 Descriptive Statistics Using Excel 143 Appendix 3. 3 Descriptive Statistics Using StatTools 146 Chapter 4 Introduction to Probability 148 Statistics in Practice: Oceanwide Seafood 149 4. 1 Experiments, Counting Rules, and Assigning Probabilities 150 Counting Rules, Combinations, and Permutations 151 Assigning Probabilities 155 Probabilities for the KP&L Project 157 4. 2 Events and Their Probabilities 160 4. 3 Some Basic Relationships of Probability 164 Complement of an Event 164 Addition Law 165 4. 4 Conditional Probability 171 Independent Events 174 Multiplication Law 174 4. Bayes’ Theorem 178 Tabular Approach 182 Summary 184 Glossary 184 xii Contents K ey Formulas 185 Supplementary Exercises 186 Case Problem: Hamilton County Judges 190 Chapter 5 Discrete Probability Distributions 193 Statistics in Practice: Citibank 194 5. 1 Random Variables 194 Discrete Random Variables 195 Continuous Random Variables 196 5. 2 Discrete Probability Distributions 197 5. 3 Expected Value and Variance 202 Expected Value 202 Variance 203 5. 4 Binomial Probability Distribution 207 A Binomial Experiment 208 Martin Clothing Store Problem 209 Using Tables of Binomial Probabilities 213 Expected Value and Variance for the Binomial Distribution 214 5. Poisson Probability Distribution 218 An Example Involving Time Intervals 218 An Example Involving Length or Distance Intervals 220 5. 6 Hypergeometric Probability Distribution 221 Summary 225 Glossary 225 Key Formulas 226 Supplementary Exercises 227 Appendix 5. 1 Discrete Probability Distributions with Minitab 230 Appendix 5. 2 Discrete Probability Distributions with Excel 230 Chapter 6 Continuous Probability D istributions 232 Statistics in Practice: Procter & Gamble 233 6. 1 Uniform Probability Distribution 234 Area as a Measure of Probability 235 6. 2 Normal Probability Distribution 238 Normal Curve 238 Standard Normal Probability Distribution 40 Computing Probabilities for Any Normal Probability Distribution 245 Grear Tire Company Problem 246 6. 3 Normal Approximation of Binomial Probabilities 250 6. 4 Exponential Probability Distribution 253 Computing Probabilities for the Exponential Distribution 254 Relationship Between the Poisson and Exponential Distributions 255 Contents xiii Summary 257 Glossary 258 Key Formulas 258 Supplementary Exercises 258 Case Problem: Specialty Toys 261 Appendix 6. 1 Continuous Probability Distributions with Minitab 262 Appendix 6. 2 Continuous Probability Distributions with Excel 263 Chapter 7 Sampling and Sampling Distributions 265 Statistics in Practice: MeadWestvaco Corporation 266 7. 1 The Electronics Associates Sampling Problem 267 7. Selecting a Sam ple 268 Sampling from a Finite Population 268 Sampling from an Infinite Population 270 7. 3 Point Estimation 273 Practical Advice 275 7. 4 Introduction to Sampling Distributions 276 _ 7. 5 Sampling Distribution of x 278 _ Expected Value of x 279 _ Standard Deviation of x 280 _ Form of the Sampling Distribution of x 281 _ Sampling Distribution of x for the EAI Problem 283 _ Practical Value of the Sampling Distribution of x 283 Relationship Between the Sample Size and the Sampling _ Distribution of x 285 _ 7. 6 Sampling Distribution of p 289 _ Expected Value of p 289 _ Standard Deviation of p 290 _ Form of the Sampling Distribution of p 291 _ Practical Value of the Sampling Distribution of p 291 7. Properties of Point Estimators 295 Unbiased 295 Efficiency 296 Consistency 297 7. 8 Other Sampling Methods 297 Stratified Random Sampling 297 Cluster Sampling 298 Systematic Sampling 298 Convenience Sampling 299 Judgment Sampling 299 Summary 300 Glossary 300 Key Formulas 301 xiv Contents Su pplementary Exercises 302 _ Appendix 7. 1 The Expected Value and Standard Deviation of x 304 Appendix 7. 2 Random Sampling with Minitab 306 Appendix 7. 3 Random Sampling with Excel 306 Appendix 7. 4 Random Sampling with StatTools 307 Chapter 8 Interval Estimation 308 Statistics in Practice: Food Lion 309 8. 1 Population Mean: Known 310 Margin of Error and the Interval Estimate 310 Practical Advice 314 8. Population Mean: Unknown 316 Margin of Error and the Interval Estimate 317 Practical Advice 320 Using a Small Sample 320 Summary of Interval Estimation Procedures 322 8. 3 Determining the Sample Size 325 8. 4 Population Proportion 328 Determining the Sample Size 330 Summary 333 Glossary 334 Key Formulas 335 Supplementary Exercises 335 Case Problem 1: Young Professional Magazine 338 Case Problem 2: Gulf Real Estate Properties 339 Case Problem 3: Metropolitan Research, Inc. 341 Appendix 8. 1 Interval Estimation with Minitab 341 Appendix 8. 2 Interval Estimation with Excel 343 Appendix 8. 3 Interval Estimation with StatTools 346 Chapter 9 Hypothesis Tests 348 Statistics in Practice: John Morrell & Company 349 9. Developing Null and Alternative Hypotheses 350 The Alternative Hypothesis as a Research Hypothesis 350 The Null Hypothesis as an Assumption to Be Challenged 351 Summary of Forms for Null and Alternative Hypotheses 352 9. 2 Type I and Type II Errors 353 9. 3 Population Mean: Known 356 One-Tailed Test 356 Two-Tailed Test 362 Summary and Practical Advice 365 Contents xv Relationship Between Interval Estimation and Hypothesis Testing 366 9. 4 Population Mean: Unknown 370 One-Tailed Test 371 Two-Tailed Test 372 Summary and Practical Advice 373 9. 5 Population Proportion 376 Summary 379 9. 6 Hypothesis Testing and Decision Making 381 9. 7 Calculating the Probability of Type II Errors 382 9. Determining the Sample Size for a Hypothesis Test About a Population Mean 387 Summary 391 Glossary 392 Key Formulas 392 Supplementary Exercises 393 Case Problem 1: Quality A ssociates, Inc. 396 Case Problem 2: Ethical Behavior of Business Students at Bayview University 397 Appendix 9. 1 Hypothesis Testing with Minitab 398 Appendix 9. 2 Hypothesis Testing with Excel 400 Appendix 9. 3 Hypothesis Testing with StatTools 404 Chapter 10 Inference About Means and Proportions with Two Populations 406 Statistics in Practice: U. S. Food and Drug Administration 407 10. 1 Inferences About the Difference Between Two Population Means: 1 and 2 Known 408 Interval Estimation of 1 – 2 408 Hypothesis Tests About 1 – 2 410 Practical Advice 412 10. Inferences About the Difference Between Two Population Means: 1 and 2 Unknown 415 Interval Estimation of 1 – 2 415 Hypothesis Tests About 1 – 2 417 Practical Advice 419 10. 3 Inferences About the Difference Between Two Population Means: Matched Samples 423 10. 4 Inferences About the Difference Between Two Population Proportions 429 Interval Estimation of p1 – p2 429 Hypothesis Tests About p1 â⠂¬â€œ p2 431 Summary 436 xvi Contents Glossary 436 Key Formulas 437 Supplementary Exercises 438 Case Problem: Par, Inc. 441 Appendix 10. 1 Inferences About Two Populations Using Minitab 442 Appendix 10. 2 Inferences About Two Populations Using Excel 444 Appendix 10. Inferences About Two Populations Using StatTools 446 Chapter 11 Inferences About Population Variances 448 Statistics in Practice: U. S. Government Accountability Office 449 11. 1 Inferences About a Population Variance 450 Interval Estimation 450 Hypothesis Testing 454 11. 2 Inferences About Two Population Variances 460 Summary 466 Key Formulas 467 Supplementary Exercises 467 Case Problem: Air Force Training Program 469 Appendix 11. 1 Population Variances with Minitab 470 Appendix 11. 2 Population Variances with Excel 470 Appendix 11. 3 Population Standard Deviation with StatTools 471 Chapter 12 Tests of Goodness of Fit and Independence 472 Statistics in Practice: United Way 473 12. Goodness of Fit Test: A Multinomial Pop ulation 474 12. 2 Test of Independence 479 12. 3 Goodness of Fit Test: Poisson and Normal Distributions 487 Poisson Distribution 487 Normal Distribution 491 Summary 496 Glossary 497 Key Formulas 497 Supplementary Exercises 497 Case Problem: A Bipartisan Agenda for Change 501 Appendix 12. 1 Tests of Goodness of Fit and Independence Using Minitab 502 Appendix 12. 2 Tests of Goodness of Fit and Independence Using Excel 503 Chapter 13 Experimental Design and Analysis of Variance 506 Statistics in Practice: Burke Marketing Services, Inc. 507 13. 1 An Introduction to Experimental Design and Analysis of Variance 508 Contents xviiData Collection 509 Assumptions for Analysis of Variance 510 Analysis of Variance: A Conceptual Overview 510 13. 2 Analysis of Variance and the Completely Randomized Design 513 Between-Treatments Estimate of Population Variance 514 Within-Treatments Estimate of Population Variance 515 Comparing the Variance Estimates: The F Test 516 ANOVA Table 518 Computer Results for Analysis of Variance 519 Testing for the Equality of k Population Means:An Observational Study 520 13. 3 Multiple Comparison Procedures 524 Fisher’s LSD 524 Type I Error Rates 527 13. 4 Randomized Block Design 530 Air Traffic Controller Stress Test 531 ANOVA Procedure 532 Computations and Conclusions 533 13. Factorial Experiment 537 ANOVA Procedure 539 Computations and Conclusions 539 Summary 544 Glossary 545 Key Formulas 545 Supplementary Exercises 547 Case Problem 1: Wentworth Medical Center 552 Case Problem 2: Compensation for Sales Professionals 553 Appendix 13. 1 Analysis of Variance with Minitab 554 Appendix 13. 2 Analysis of Variance with Excel 555 Appendix 13. 3 Analysis of Variance with StatTools 557 Chapter 14 Simple Linear Regression 560 Statistics in Practice: Alliance Data Systems 561 14. 1 Simple Linear Regression Model 562 Regression Model and Regression Equation 562 Estimated Regression Equation 563 14. 2 Least Squares Method 565 14. Coefficient of Determ ination 576 Correlation Coefficient 579 14. 4 Model Assumptions 583 14. 5 Testing for Significance 585 Estimate of 2 585 t Test 586 xviii Contents Confidence Interval for 1 587 F Test 588 Some Cautions About the Interpretation of Significance Tests 590 14. 6 Using the Estimated Regression Equation for Estimation and Prediction 594 Point Estimation 594 Interval Estimation 594 Confidence Interval for the Mean Value of y 595 Prediction Interval for an Individual Value of y 596 14. 7 Computer Solution 600 14. 8 Residual Analysis: Validating Model Assumptions 605 Residual Plot Against x 606 Residual Plot Against y 607 ? Standardized Residuals 607 Normal Probability Plot 610 14. Residual Analysis: Outliers and Influential Observations 614 Detecting Outliers 614 Detecting Influential Observations 616 Summary 621 Glossary 622 Key Formulas 623 Supplementary Exercises 625 Case Problem 1: Measuring Stock Market Risk 631 Case Problem 2: U. S. Department of Transportation 632 Case Problem 3: Alu mni Giving 633 Case Problem 4: PGA Tour Statistics 633 Appendix 14. 1 Calculus-Based Derivation of Least Squares Formulas 635 Appendix 14. 2 A Test for Significance Using Correlation 636 Appendix 14. 3 Regression Analysis with Minitab 637 Appendix 14. 4 Regression Analysis with Excel 638 Appendix 14. 5 Regression Analysis with StatTools 640 Chapter 15 Multiple Regression 642 Statistics in Practice: dunnhumby 643 15. 1 Multiple Regression Model 644 Regression Model and Regression Equation 644 Estimated Multiple Regression Equation 644 15. Least Squares Method 645 An Example: Butler Trucking Company 646 Note on Interpretation of Coefficients 648 15. 3 Multiple Coefficient of Determination 654 15. 4 Model Assumptions 657 Contents xix 15. 5 Testing for Significance 658 F Test 658 t Test 661 Multicollinearity 662 15. 6 Using the Estimated Regression Equation for Estimation and Prediction 665 15. 7 Categorical Independent Variables 668 An Example: Johnson Filtration, Inc. 668 Interpreting the Parameters 670 More Complex Categorical Variables 672 15. 8 Residual Analysis 676 Detecting Outliers 678 Studentized Deleted Residuals and Outliers 678 Influential Observations 679 Using Cook’s Distance Measure to Identify Influential Observations 679 15. Logistic Regression 683 Logistic Regression Equation 684 Estimating the Logistic Regression Equation 685 Testing for Significance 687 Managerial Use 688 Interpreting the Logistic Regression Equation 688 Logit Transformation 691 Summary 694 Glossary 695 Key Formulas 696 Supplementary Exercises 698 Case Problem 1: Consumer Research, Inc. 704 Case Problem 2: Alumni Giving 705 Case Problem 3: PGA Tour Statistics 705 Case Problem 4: Predicting Winning Percentage for the NFL 708 Appendix 15. 1 Multiple Regression with Minitab 708 Appendix 15. 2 Multiple Regression with Excel 709 Appendix 15. 3 Logistic Regression with Minitab 710 Appendix 15. 4 Multiple Regression with StatTools 711Chapter 16 Regression Analysis: Model Buildi ng 712 Statistics in Practice: Monsanto Company 713 16. 1 General Linear Model 714 Modeling Curvilinear Relationships 714 Interaction 718 xx Contents Transformations Involving the Dependent Variable 720 Nonlinear Models That Are Intrinsically Linear 724 16. 2 Determining When to Add or Delete Variables 729 General Case 730 Use of p-Values 732 16. 3 Analysis of a Larger Problem 735 16. 4 Variable Selection Procedures 739 Stepwise Regression 739 Forward Selection 740 Backward Elimination 741 Best-Subsets Regression 741 Making the Final Choice 742 16. 5 Multiple Regression Approach to Experimental Design 745 16. Autocorrelation and the Durbin-Watson Test 750 Summary 754 Glossary 754 Key Formulas 754 Supplementary Exercises 755 Case Problem 1: Analysis of PGA Tour Statistics 758 Case Problem 2: Fuel Economy for Cars 759 Appendix 16. 1 Variable Selection Procedures with Minitab 760 Appendix 16. 2 Variable Selection Procedures with StatTools 761 Chapter 17 Index Numbers 763 Statistics in Practice: U. S. Department of Labor, Bureau of Labor Statistics 764 17. 1 Price Relatives 765 17. 2 Aggregate Price Indexes 765 17. 3 Computing an Aggregate Price Index from Price Relatives 769 17. 4 Some Important Price Indexes 771 Consumer Price Index 771 Producer Price Index 771 Dow Jones Averages 772 17. 5 Deflating a Series by Price Indexes 773 17. 6 Price Indexes: Other Considerations 777 Selection of Items 777 Selection of a Base Period 777 Quality Changes 777 17. Quantity Indexes 778 Summary 780 Contents xxi Glossary 780 Key Formulas 780 Supplementary Exercises 781 Chapter 18 Time Series Analysis and Forecasting 784 Statistics in Practice: Nevada Occupational Health Clinic 785 18. 1 Time Series Patterns 786 Horizontal Pattern 786 Trend Pattern 788 Seasonal Pattern 788 Trend and Seasonal Pattern 789 Cyclical Pattern 789 Selecting a Forecasting Method 791 18. 2 Forecast Accuracy 792 18. 3 Moving Averages and Exponential Smoothing 797 Moving Averages 797 Weighted Moving Average s 800 Exponential Smoothing 800 18. 4 Trend Projection 807 Linear Trend Regression 807 Holt’s Linear Exponential Smoothing 812 Nonlinear Trend Regression 814 18. Seasonality and Trend 820 Seasonality Without Trend 820 Seasonality and Trend 823 Models Based on Monthly Data 825 18. 6 Time Series Decomposition 829 Calculating the Seasonal Indexes 830 Deseasonalizing the Time Series 834 Using the Deseasonalized Time Series to Identify Trend 834 Seasonal Adjustments 836 Models Based on Monthly Data 837 Cyclical Component 837 Summary 839 Glossary 840 Key Formulas 841 Supplementary Exercises 842 Case Problem 1: Forecasting Food and Beverage Sales 846 Case Problem 2: Forecasting Lost Sales 847 Appendix 18. 1 Forecasting with Minitab 848 Appendix 18. 2 Forecasting with Excel 851 Appendix 18. 3 Forecasting with StatTools 852 xxii Contents Chapter 19 Nonparametric Methods 855 Statistics in Practice: West Shell Realtors 856 19. Sign Test 857 Hypothesis Test About a Population Median 857 Hypothesis Test with Matched Samples 862 19. 2 Wilcoxon Signed-Rank Test 865 19. 3 Mann-Whitney-Wilcoxon Test 871 19. 4 Kruskal-Wallis Test 882 19. 5 Rank Correlation 887 Summary 891 Glossary 892 Key Formulas 893 Supplementary Exercises 893 Appendix 19. 1 Nonparametric Methods with Minitab 896 Appendix 19. 2 Nonparametric Methods with Excel 899 Appendix 19. 3 Nonparametric Methods with StatTools 901 Chapter 20 Statistical Methods for Quality Control 903 Statistics in Practice: Dow Chemical Company 904 20. 1 Philosophies and Frameworks 905 Malcolm Baldrige National Quality Award 906 ISO 9000 906 Six Sigma 906 20. Statistical Process Control 908 Control Charts 909 _ x Chart: Process Mean and Standard Deviation Known 910 _ x Chart: Process Mean and Standard Deviation Unknown 912 R Chart 915 p Chart 917 np Chart 919 Interpretation of Control Charts 920 20. 3 Acceptance Sampling 922 KALI, Inc. : An Example of Acceptance Sampling 924 Computing the Probability of Accepting a Lot 924 Select ing an Acceptance Sampling Plan 928 Multiple Sampling Plans 930 Summary 931 Glossary 931 Key Formulas 932 Supplementary Exercises 933 Appendix 20. 1 Control Charts with Minitab 935 Appendix 20. 2 Control Charts with StatTools 935 Contents xxiii Chapter 21 Decision Analysis 937 Statistics in Practice: Ohio Edison Company 938 21. Problem Formulation 939 Payoff Tables 940 Decision Trees 940 21. 2 Decision Making with Probabilities 941 Expected Value Approach 941 Expected Value of Perfect Information 943 21. 3 Decision Analysis with Sample Information 949 Decision Tree 950 Decision Strategy 951 Expected Value of Sample Information 954 21. 4 Computing Branch Probabilities Using Bayes’ Theorem 960 Summary 964 Glossary 965 Key Formulas 966 Supplementary Exercises 966 Case Problem: Lawsuit Defense Strategy 969 Appendix: An Introduction to PrecisionTree 970 Chapter 22 Sample Survey On Website Statistics in Practice: Duke Energy 22-2 22. 1 Terminology Used in Sample Surveys 22-2 22. 2 Types of Surveys and Sampling Methods 22-3 22. Survey Errors 22-5 Nonsampling Error 22-5 Sampling Error 22-5 22. 4 Simple Random Sampling 22-6 Population Mean 22-6 Population Total 22-7 Population Proportion 22-8 Determining the Sample Size 22-9 22. 5 Stratified Simple Random Sampling 22-12 Population Mean 22-12 Population Total 22-14 Population Proportion 22-15 Determining the Sample Size 22-16 22. 6 Cluster Sampling 22-21 Population Mean 22-23 Population Total 22-24 Population Proportion 22-25 Determining the Sample Size 22-26 22. 7 Systematic Sampling 22-29 Summary 22-29 xxiv Contents Glossary 22-30 Key Formulas 22-30 Supplementary Exercises 22-34 Appendix: Self-Test Solutions and Answers to Even-Numbered Exercises 22-37Appendix A References and Bibliography 976 Appendix B Tables 978 Appendix C Summation Notation 1005 Appendix D Self-Test Solutions and Answers to Even-Numbered Exercises 1007 Appendix E Using Excel Functions 1062 Appendix F Computing p-Values Using Minitab and Exc el 1067 Index 1071 Preface The purpose of STATISTICS FOR BUSINESS AND ECONOMICS is to give students, primarily those in the fields of business administration and economics, a conceptual introduction to the field of statistics and its many applications. The text is applications oriented and written with the needs of the nonmathematician in mind; the mathematical prerequisite is knowledge of algebra.Applications of data analysis and statistical methodology are an integral part of the organization and presentation of the text material. The discussion and development of each technique is presented in an application setting, with the statistical results providing insights to decisions and solutions to problems. Although the book is applications oriented, we have taken care to provide sound methodological development and to use notation that is generally accepted for the topic being covered. Hence, students will find that this text provides good preparation for the study of more advanced statistical material. A bibliography to guide further study is included as an appendix.The text introduces the student to the software packages of Minitab 15 and Microsoft ® Office Excel 2007 and emphasizes the role of computer software in the application of statistical analysis. Minitab is illustrated as it is one of the leading statistical software packages for both education and statistical practice. Excel is not a statistical software package, but the wide availability and use of Excel make it important for students to understand the statistical capabilities of this package. Minitab and Excel procedures are provided in appendixes so that instructors have the flexibility of using as much computer emphasis as desired for the course.Changes in the Eleventh Edition We appreciate the acceptance and positive response to the previous editions of STATISTICS FOR BUSINESS AND ECONOMICS. Accordingly, in making modifications for this new edition, we have maintained the presentation style and readability of those editions. The significant changes in the new edition are summarized here. Content Revisions †¢ Revised Chapter 18 — â€Å"Time Series Analysis and Forecasting. † The chapter has been completely rewritten to focus more on using the pattern in a time series plot to select an appropriate forecasting method. We begin with a new Section 18. 1 on time series patterns, followed by a new Section 18. on methods for measuring forecast accuracy. Section 18. 3 discusses moving averages and exponential smoothing. Section 18. 4 introduces methods appropriate for a time series that exhibits a trend. Here we illustrate how regression analysis and Holt’s linear exponential smoothing can be used for linear trend projection, and then discuss how regression analysis can be used to model nonlinear relationships involving a quadratic trend and an exponential growth. Section 18. 5 then shows how dummy variables can be used to model seasonality in a foreca sting equation. Section 18. 6 discusses classical time series decomposition, including the concept of deseasonalizing a time series.There is a new appendix on forecasting using the Excel add-in StatTools and most exercises are new or updated. †¢ Revised Chapter 19 — â€Å"Nonparametric Methods. † The treatment of nonparametric methods has been revised and updated. We contrast each nonparametric method xxvi Preface †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ with its parametric counterpart and describe how fewer assumptions are required for the nonparametric procedure. The sign test emphasizes the test for a population median, which is important in skewed populations where the median is often the preferred measure of central location. The Wilcoxon Rank-Sum test is used for both matched samples tests and tests about a median of a symmetric population.A new small-sample application of the Mann-Whitney-Wilcoxon test shows the exact sampling distrib ution of the test statistic and is used to explain why the sum of the signed ranks can be used to test the hypothesis that the two populations are identical. The chapter concludes with the Kruskal-Wallis test and rank correlation. New chapter ending appendixes describe how Minitab, Excel, and StatTools can be used to implement nonparametric methods. Twenty-seven data sets are now available to facilitate computer solution of the exercises. StatTools Add-In for Excel. Excel 2007 does not contain statistical functions or data analysis tools to perform all the statistical procedures discussed in the text.StatTools is a commercial Excel 2007 add-in, developed by Palisades Corporation, that extends the range of statistical options for Excel users. In an appendix to Chapter 1 we show how to download and install StatTools, and most chapters include a chapter appendix that shows the steps required to accomplish a statistical procedure using StatTools. We have been very careful to make the us e of StatTools completely optional so that instructors who want to teach using the standard tools available in Excel 2007 can continue to do so. But users who want additional statistical capabilities not available in standard Excel 2007 now have access to an industry standard statistics add-in that students will be able to continue to use in the workplace. Change in Terminology for Data.In the previous edition, nominal and ordinal data were classified as qualitative; interval and ratio data were classified as quantitative. In this edition, nominal and ordinal data are referred to as categorical data. Nominal and ordinal data use labels or names to identify categories of like items. Thus, we believe that the term categorical is more descriptive of this type of data. Introducing Data Mining. A new section in Chapter 1 introduces the relatively new field of data mining. We provide a brief overview of data mining and the concept of a data warehouse. We also describe how the fields of st atistics and computer science join to make data mining operational and valuable. Ethical Issues in Statistics.Another new section in Chapter 1 provides a discussion of ethical issues when presenting and interpreting statistical information. Updated Excel Appendix for Tabular and Graphical Descriptive Statistics. The chapter-ending Excel appendix for Chapter 2 shows how the Chart Tools, PivotTable Report, and PivotChart Report can be used to enhance the capabilities for displaying tabular and graphical descriptive statistics. Comparative Analysis with Box Plots. The treatment of box plots in Chapter 2 has been expanded to include relatively quick and easy comparisons of two or more data sets. Typical starting salary data for accounting, finance, management, and marketing majors are used to illustrate box plot multigroup comparisons. Revised Sampling Material.The introduction of Chapter 7 has been revised and now includes the concepts of a sampled population and a frame. The distincti on between sampling from a finite population and an infinite population has been clarified, with sampling from a process used to illustrate the selection of a random sample from an infinite population. A practical advice section stresses the importance of obtaining close correspondence between the sampled population and the target population. Revised Introduction to Hypothesis Testing. Section 9. 1, Developing Null and Alternative Hypotheses, has been revised. A better set of guidelines has been developed for identifying the null and alternative hypotheses.The context of the situation and the purpose for taking the sample are key. In situations in which the Preface xxvii †¢ †¢ †¢ †¢ focus is on finding evidence to support a research finding, the research hypothesis is the alternative hypothesis. In situations where the focus is on challenging an assumption, the assumption is the null hypothesis. New PrecisionTree Software for Decision Analysis. PrecisionTree is a nother Excel add-in developed by Palisades Corporation that is very helpful in decision analysis. Chapter 21 has a new appendix which shows how to use the PrecisionTree add-in. New Case Problems. We have added 5 new case problems to this edition, bringing the total number of case problems to 31.A new case problem on descriptive statistics appears in Chapter 3 and a new case problem on hypothesis testing appears in Chapter 9. Three new case problems have been added to regression in Chapters 14, 15, and 16. These case problems provide students with the opportunity to analyze larger data sets and prepare managerial reports based on the results of the analysis. New Statistics in Practice Applications. Each chapter begins with a Statistics in Practice vignette that describes an application of the statistical methodology to be covered in the chapter. New to this edition are Statistics in Practice articles for Oceanwide Seafood in Chapter 4 and the London-based marketing services company d unnhumby in Chapter 15. New Examples and Exercises Based on Real Data.We continue to make a significant effort to update our text examples and exercises with the most current real data and referenced sources of statistical information. In this edition, we have added approximately 150 new examples and exercises based on real data and referenced sources. Using data from sources also used by The Wall Street Journal, USA Today, Barron’s, and others, we have drawn from actual studies to develop explanations and to create exercises that demonstrate the many uses of statistics in business and economics. We believe that the use of real data helps generate more student interest in the material and enables the student to learn about both the statistical methodology and its application. The eleventh edition of the text contains over 350 examples and exercises based on real data.Features and Pedagogy Authors Anderson, Sweeney, and Williams have continued many of the features that appeare d in previous editions. Important ones for students are noted here. Methods Exercises and Applications Exercises The end-of-section exercises are split into two parts, Methods and Applications. The Methods exercises require students to use the formulas and make the necessary computations. The Applications exercises require students to use the chapter material in real-world situations. Thus, students first focus on the computational â€Å"nuts and bolts† and then move on to the subtleties of statistical application and interpretation. Self-Test ExercisesCertain exercises are identified as â€Å"Self-Test Exercises. † Completely worked-out solutions for these exercises are provided in Appendix D at the back of the book. Students can attempt the Self-Test Exercises and immediately check the solution to evaluate their understanding of the concepts presented in the chapter. Margin Annotations and Notes and Comments Margin annotations that highlight key points and provide ad ditional insights for the student are a key feature of this text. These annotations, which appear in the margins, are designed to provide emphasis and enhance understanding of the terms and concepts being presented in the text. xxviii PrefaceAt the end of many sections, we provide Notes and Comments designed to give the student additional insights about the statistical methodology and its application. Notes and Comments include warnings about or limitations of the methodology, recommendations for application, brief descriptions of additional technical considerations, and other matters. Data Files Accompany the Text Over 200 data files are available on the website that accompanies the text. The data sets are available in both Minitab and Excel formats. File logos are used in the text to identify the data sets that are available on the website. Data sets for all case problems as well as data sets for larger exercises are included. Acknowledgments A special thank you goes to Jeffrey D. Camm, University of Cincinnati, and James J.Cochran, Louisiana Tech University, for their contributions to this eleventh edition of Statistics for Business and Economics. Professors Camm and Cochran provided extensive input for the new chapters on forecasting and nonparametric methods. In addition, they provided helpful input and suggestions for new case problems, exercises, and Statistics in Practice articles. We would also like to thank our associates from business and industry who supplied the Statistics in Practice features. We recognize them individually by a credit line in each of the articles. Finally, we are also indebted to our senior acquisitions editor Charles McCormick, Jr. , our developmental editor Maggie Kubale, our content project manager, Jacquelyn K Featherly, our marketing manager Bryant T.Chrzan, and others at Cengage South-Western for their editorial counsel and support during the preparation of this text. David R. Anderson Dennis J. Sweeney Thomas A. Williams About the Authors David R. Anderson. David R. Anderson is Professor of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. Born in Grand Forks, North Dakota, he earned his B. S. , M. S. , and Ph. D. degrees from Purdue University. Professor Anderson has served as Head of the Department of Quantitative Analysis and Operations Management and as Associate Dean of the College of Business Administration at the University of Cincinnati. In addition, he was the coordinator of the College’s first Executive Program.At the University of Cincinnati, Professor Anderson has taught introductory statistics for business students as well as graduate-level courses in regression analysis, multivariate analysis, and management science. He has also taught statistical courses at the Department of Labor in Washington, D. C. He has been honored with nominations and awards for excellence in teaching and excellence in service to student organizations. Profe ssor Anderson has coauthored 10 textbooks in the areas of statistics, management science, linear programming, and production and operations management. He is an active consultant in the field of sampling and statistical methods. Dennis J.Sweeney. Dennis J. Sweeney is Professor of Quantitative Analysis and Founder of the Center for Productivity Improvement at the University of Cincinnati. Born in Des Moines, Iowa, he earned a B. S. B. A. degree from Drake University and his M. B. A. and D. B. A. degrees from Indiana University, where he was an NDEA Fellow. During 1978–79, Professor Sweeney worked in the management science group at Procter & Gamble; during 1981–82, he was a visiting professor at Duke University. Professor Sweeney served as Head of the Department of Quantitative Analysis and as Associate Dean of the College of Business Administration at the University of Cincinnati.Professor Sweeney has published more than 30 articles and monographs in the area of managem ent science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger, and Cincinnati Gas & Electric have funded his research, which has been published in Management Science, Operations Research, Mathematical Programming, Decision Sciences, and other journals. Professor Sweeney has coauthored 10 textbooks in the areas of statistics, management science, linear programming, and production and operations management. Thomas A. Williams. Thomas A. Williams is Professor of Management Science in the College of Business at Rochester Institute of Technology.Born in Elmira, New York, he earned his B. S. degree at Clarkson University. He did his graduate work at Rensselaer Polytechnic Institute, where he received his M. S. and Ph. D. degrees. Before joining the College of Business at RIT, Professor Williams served for seven years as a faculty member in the College of Business Administration at the University of Cincinnati, where he developed th e undergraduate program in Information Systems and then served as its coordinator. At RIT he was the first chairman of the Decision Sciences Department. He teaches courses in management science and statistics, as well as graduate courses in regression and decision analysis.Professor Williams is the coauthor of 11 textbooks in the areas of management science, statistics, production and operations management, and mathematics. He has been a consultant for numerous Fortune 500 companies and has worked on projects ranging from the use of data analysis to the development of large-scale regression models. This page intentionally left blank STATISTICS FOR BUSINESS AND ECONOMICS 11e This page intentionally left blank CHAPTER Data and Statistics CONTENTS STATISTICS IN PRACTICE: BUSINESSWEEK 1. 1 APPLICATIONS IN BUSINESS AND ECONOMICS Accounting Finance Marketing Production Economics DATA Elements, Variables, and Observations Scales of Measurement Categorical and Quantitative Data Cross-Sectio nal and Time Series Data 1. DATA SOURCES Existing Sources Statistical Studies Data Acquisition Errors DESCRIPTIVE STATISTICS STATISTICAL INFERENCE COMPUTERS AND STATISTICAL ANALYSIS DATA MINING ETHICAL GUIDELINES FOR STATISTICAL PRACTICE 1 1. 4 1. 5 1. 6 1. 7 1. 8 1. 2 2 Chapter 1 Data and Statistics STATISTICS in PRACTICE NEW YORK, NEW YORK BUSINESSWEEK* With a global circulation of more than 1 million, BusinessWeek is the most widely read business magazine in the world. More than 200 dedicated reporters and editors in 26 bureaus worldwide deliver a variety of articles of interest to the business and economic community. Along with feature articles on current topics, the magazine contains regular sections on International Business, Economic Analysis, Information Processing, and Science & Technology.Information in the feature articles and the regular sections helps readers stay abreast of current developments and assess the impact of those developments on business and economic condit ions. Most issues of BusinessWeek provide an in-depth report on a topic of current interest. Often, the in-depth reports contain statistical facts and summaries that help the reader understand the business and economic information. For example, the February 23, 2009 issue contained a feature article about the home foreclosure crisis, the March 17, 2009 issue included a discussion of when the stock market would begin to recover, and the May 4, 2009 issue had a special report on how to make pay cuts less painful.In addition, the weekly BusinessWeek Investor provides statistics about the state of the economy, including production indexes, stock prices, mutual funds, and interest rates. BusinessWeek also uses statistics and statistical information in managing its own business. For example, an annual survey of subscribers helps the company learn about subscriber demographics, reading habits, likely purchases, lifestyles, and so on. BusinessWeek managers use statistical summaries from the survey to provide better services to subscribers and advertisers. One recent North *The authors are indebted to Charlene Trentham, Research Manager at BusinessWeek, for providing this Statistics in Practice. BusinessWeek uses statistical facts and summaries in many of its articles.  © Terri Miller/E-Visual Communications, Inc.American subscriber survey indicated that 90% of BusinessWeek subscribers use a personal computer at home and that 64% of BusinessWeek subscribers are involved with computer purchases at work. Such statistics alert BusinessWeek managers to subscriber interest in articles about new developments in computers. The results of the survey are also made available to potential advertisers. The high percentage of subscribers using personal computers at home and the high percentage of subscribers involved with computer purchases at work would be an incentive for a computer manufacturer to consider advertising in BusinessWeek. In this chapter, we discuss the types of d ata available for statistical analysis and describe how the data are obtained.We introduce descriptive statistics and statistical inference as ways of converting data into meaningful and easily interpreted statistical information. Frequently, we see the following types of statements in newspapers and magazines: †¢ The National Association of Realtors reported that the median price paid by firsttime home buyers is $165,000 (The Wall Street Journal, February 11, 2009). †¢ NCAA president Myles Brand reported that college athletes are earning degrees at record rates. Latest figures show that 79% of all men and women student-athletes graduate (Associated Press, October 15, 2008). †¢ The average one-way travel time to work is 25. 3 minutes (U. S. Census Bureau, March 2009). 1. 1 Applications in Business and Economics 3 †¢ A record high 11% of U. S. omes are vacant, a glut created by the housing boom and subsequent collapse (USA Today, February 13, 2009). †¢ The na tional average price for regular gasoline reached $4. 00 per gallon for the first time in history (Cable News Network website, June 8, 2008). †¢ The New York Yankees have the highest salaries in major league baseball. The total payroll is $201,449,289 with a median salary of $5,000,000 (USA Today Salary Data Base, April 2009). †¢ The Dow Jones Industrial Average closed at 8721 (The Wall Street Journal, June 2, 2009). The numerical facts in the preceding statements ($165,000, 79%, 25. 3, 11%, $4. 00, $201,449,289, $5,000,000 and 8721) are called statistics.In this usage, the term statistics refers to numerical facts such as averages, medians, percents, and index numbers that help us understand a variety of business and economic situations. However, as you will see, the field, or subject, of statistics involves much more than numerical facts. In a broader sense, statistics is defined as the art and science of collecting, analyzing, presenting, and interpreting data. Particul arly in business and economics, the information provided by collecting, analyzing, presenting, and interpreting data gives managers and decision makers a better understanding of the business and economic environment and thus enables them to make more informed and better decisions. In this text, we emphasize the use of statistics for business and economic decision making.Chapter 1 begins with some illustrations of the applications of statistics in business and economics. In Section 1. 2 we define the term data and introduce the concept of a data set. This section also introduces key terms such as variables and observations, discusses the difference between quantitative and categorical data, and illustrates the uses of cross-sectional and time series data. Section 1. 3 discusses how data can be obtained from existing sources or through survey and experimental studies designed to obtain new data. The important role that the Internet now plays in obtaining data is also highlighted. The uses of data in developing descriptive statistics and in making statistical inferences are described in Sections 1. 4 and 1. 5.The last three sections of Chapter 1 provide the role of the computer in statistical analysis, an introduction to the relative new field of data mining, and a discussion of ethical guidelines for statistical practice. A chapter-ending appendix includes an introduction to the add-in StatTools which can be used to extend the statistical options for users of Microsoft Excel. 1. 1 Applications in Business and Economics In today’s global business and economic environment, anyone can access vast amounts of statistical information. The most successful managers and decision makers understand the information and know how to use it effectively. In this section, we provide examples that illustrate some of the uses of statistics in business and economics. Accounting Public accounting firms use statistical sampling procedures when conducting audits for their clien ts.For instance, suppose an accounting firm wants to determine whether the amount of accounts receivable shown on a client’s balance sheet fairly represents the actual amount of accounts receivable. Usually the large number of individual accounts receivable makes reviewing and validating every account too time-consuming and expensive. As common practice in such situations, the audit staff selects a subset of the accounts called a sample. After reviewing the accuracy of the sampled accounts, the auditors draw a conclusion as to whether the accounts receivable amount shown on the client’s balance sheet is acceptable. 4 Chapter 1 Data and Statistics Finance Financial analysts use a variety of statistical information to guide their investment recommendations.In the case of stocks, the analysts review a variety of financial data including price/earnings ratios and dividend yields. By comparing the information for an individual stock with information about the stock market a verages, a financial analyst can begin to draw a conclusion as to whether an individual stock is over- or underpriced. For example, Barron’s (February 18, 2008) reported that the average dividend yield for the 30 stocks in the Dow Jones Industrial Average was 2. 45%. Altria Group showed a dividend yield of 3. 05%. In this case, the statistical information on dividend yield indicates a higher dividend yield for Altria Group than the average for the Dow Jones stocks. Therefore, a financial analyst might conclude that Altria Group was underpriced.This and other information about Altria Group would help the analyst make a buy, sell, or hold recommendation for the stock. Marketing Electronic scanners at retail checkout counters collect data for a variety of marketing research applications. For example, data suppliers such as ACNielsen and Information Resources, Inc. , purchase point-of-sale scanner data from grocery stores, process the data, and then sell statistical summaries of the data to manufacturers. Manufacturers spend hundreds of thousands of dollars per product category to obtain this type of scanner data. Manufacturers also purchase data and statistical summaries on promotional activities such as special pricing and the use of in-store displays.Brand managers can review the scanner statistics and the promotional activity statistics to gain a better understanding of the relationship between promotional activities and sales. Such analyses often prove helpful in establishing future marketing strategies for the various products. Production Today’s emphasis on quality makes quality control an important application of statistics in production. A variety of statistical quality control charts are used to monitor the output of a production process. In particular, an x-bar chart can be used to monitor the average output. Suppose, for example, that a machine fills containers with 12 ounces of a soft drink. Periodically, a production worker selects a sa mple of containers and computes the average number of ounces in the sample.This average, or x-bar value, is plotted on an x-bar chart. A plotted value above the chart’s upper control limit indicates overfilling, and a plotted value below the chart’s lower control limit indicates underfilling. The process is termed â€Å"in control† and allowed to continue as long as the plotted x-bar values fall between the chart’s upper and lower control limits. Properly interpreted, an x-bar chart can help determine when adjustments are necessary to correct a production process. Economics Economists frequently provide forecasts about the future of the economy or some aspect of it. They use a variety of statistical information in making such forecasts.For instance, in forecasting inflation rates, economists use statistical information on such indicators as the Producer Price Index, the unemployment rate, and manufacturing capacity utilization. Often these statistical ind icators are entered into computerized forecasting models that predict inflation rates. Applications of statistics such as those described in this section are an integral part of this text. Such examples provide an overview of the breadth of statistical applications. To supplement these examples, practitioners in the fields of business and economics provided chapter-opening Statistics in Practice articles that introduce the material covered in each chapter.The Statistics in Practice applications show the importance of statistics in a wide variety of business and economic situations. 1. 2 Data 5 1. 2 Data Data are the facts and figures collected, analyzed, and summarized for presentation and interpretation. All the data collected in a particular study are referred to as the data set for the study. Table 1. 1 shows a data set containing information for 25 mutual funds that are part of the Morningstar Funds500 for 2008. Morningstar is a company that tracks over 7000 mutual funds and pre pares in-depth analyses of 2000 of these. Their recommendations are followed closely by financial analysts and individual investors. Elements, Variables, and Observations Elements are the entities on which data are collected.For the data set in Table 1. 1 each individual mutual fund is an element: the element names appear in the first column. With 25 mutual funds, the data set contains 25 elements. A variable is a characteristic of interest for the elements. The data set in Table 1. 1 includes the following five variables: †¢ Fund Type: The type of mutual fund, labeled DE (Domestic Equity), IE (International Equity), and FI (Fixed Income) †¢ Net Asset Value ($): The closing price per share on December 31, 2007 TABLE 1. 1 DATA SET FOR 25 MUTUAL FUNDS 5-Year Expense Net Asset Average Ratio Morningstar Value ($) Return (%) (%) Rank 14. 37 10. 73 24. 94 16. 92 35. 73 13. 47 73. 1 48. 39 45. 60 8. 60 49. 81 15. 30 17. 44 27. 86 40. 37 10. 68 26. 27 53. 89 22. 46 37. 53 12. 10 2 4. 42 15. 68 32. 58 35. 41 30. 53 3. 34 10. 88 15. 67 15. 85 17. 23 17. 99 23. 46 13. 50 2. 76 16. 70 15. 31 15. 16 32. 70 9. 51 13. 57 23. 68 51. 10 16. 91 15. 46 4. 31 13. 41 2. 37 17. 01 13. 98 1. 41 0. 49 0. 99 1. 18 1. 20 0. 53 0. 89 0. 90 0. 89 0. 45 1. 36 1. 32 1. 31 1. 16 1. 05 1. 25 1. 36 1. 24 0. 80 1. 27 0. 62 0. 29 0. 16 0. 23 1. 19 3-Star 4-Star 3-Star 3-Star 4-Star 3-Star 5-Star 4-Star 3-Star 3-Star 4-Star 3-Star 5-Star 3-Star 2-Star 3-Star 4-Star 4-Star 4-Star 4-Star 3-Star 4-Star 3-Star 3-Star 4-Star Fund Name American Century Intl.Disc American Century Tax-Free Bond American Century Ultra Artisan Small Cap Brown Cap Small DFA U. S. Micro Cap Fidelity Contrafund Fidelity Overseas Fidelity Sel Electronics Fidelity Sh-Term Bond Gabelli Asset AAA Kalmar Gr Val Sm Cp Marsico 21st Century Mathews Pacific Tiger Oakmark I PIMCO Emerg Mkts Bd D RS Value A T. Rowe Price Latin Am. T. Rowe Price Mid Val Thornburg Value A USAA Income Vanguard Equity-Inc Vanguard Sht-Tm TE Vangua rd Sm Cp Idx Wasatch Sm Cp Growth Fund Type IE FI DE DE DE DE DE IE DE FI DE DE DE IE DE FI DE IE DE DE FI DE FI DE DE WEB file Morningstar Data sets such as Morningstar are available on the website for this text. Source: Morningstar Funds500 (2008). 6 Chapter 1Data and Statistics †¢ 5-Year Average Return (%): The average annual return for the fund over the past 5 years †¢ Expense Ratio: The percentage of assets deducted each fiscal year for fund expenses †¢ Morningstar Rank: The overall risk-adjusted star rating for each fund; Morningstar ranks go from a low of 1-Star to a high of 5-Stars Measurements collected on each variable for every element in a study provide the data. The set of measurements obtained for a particular element is called an observation. Referring to Table 1. 1 we see that the set of measurements for the first observation (American Century Intl. Disc) is IE, 14. 37, 30. 53, 1. 41, and 3-Star.The set of measurements for the second observation (Ameri can Century Tax-Free Bond) is FI, 10. 73, 3. 34, 0. 49, and 4-Star, and so on. A data set with 25 elements contains 25 observations. Scales of Measurement Data collection requires one of the following scales of measurement: nominal, ordinal, interval, or ratio. The scale of measurement determines the amount of information contained in the data and indicates the most appropriate data summarization and statistical analyses. When the data for a variable consist of labels or names used to identify an attribute of the element, the scale of measurement is considered a nominal scale. For example, referring to the data in Table 1. , we see that the scale of measurement for the Fund Type variable is nominal because DE, IE, and FI are labels used to identify the category or type of fund. In cases where the scale of measurement is nominal, a numeric code as well as nonnumeric labels may be used. For example, to facilitate data collection and to prepare the data for entry into a computer databa se, we might use a numeric code by letting 1 denote Domestic Equity, 2 deno