Business - Return on Equity Essay Example | Topics and Well Written Essays - 750 words

Violence In Society Essays - Domestic Violence, Abuse, Crime

Viciousness In Society Essays - Domestic Violence, Abuse, Crime Viciousness In Society Viciousness in Society The main response to catching wind of the subject of battered men, individuals will in general consider it being totally bogus or exceptionally unprecedented. Battered spouses are a point for jokes since individuals consistently expect that it is the ladies who are battered. One analyst noticed that spouses were the culprits in seventy-three percent of the portrayals of aggressive behavior at home in paper funnies. Battered spouses have generally been either disregarded or on the other hand exposed to criticism and misuse. Indeed, even those of us who like to consider ourselves freed and receptive regularly make some troublesome memories even envisioning that spouse battering could happen. In spite of the fact that woman's rights has opened a large number of our eyes about the presence of abusive behavior at home, the maltreatment of spouses is an infrequently talked about wonder. One explanation that spouse battering isn't examined is that it is an uncommon event. Another reason is that since ladies were viewed as more fragile and more powerless than men relating to sex jobs, and men then again were viewed as increasingly tough also, independent. The investigation of mishandled spouses is viewed as immaterial. In 1974, explore was done to analyze male and female abusive behavior at home. In this investigation, it was discovered that forty seven percent of spouses had utilized physical brutality on their spouses, and thirty-three percent of wives had utilized brutality on their husbands(Gelles 1974). Likewise in 1974, an investigation was discharged indicating that the quantity of murders of ladies by men was about equivalent to the number of murders of men by ladies. In spite of the fact that it had at long last been indicated that there was savagery being executed both by spouses and husbands, there was no proof about the seriousness or who started the maltreatment and who is acting in self-preservation. The possibility of ladies being savage is a hard thing for some individuals to accept. It conflicts with the generalization of the inactive and powerless female. This, notwithstanding the way that ladies are known to be more probable than men to submit kid misuse and kid murder. Laws about aggressive behavior at home is consistently orientated toward the female casualty. Society expresses that the lady experience the ill effects of misuse. These reasons clarify why most manhandled men, regardless of how able they are of doing as such, offer almost no protection from their accomplices' physical brutality. Also, numerous ladies, very much aware of these feelings of dread, may as a matter of fact proceed with their maltreatment, realizing they can pull off it. While battered men discover not many offices or backing, there are an assortment of projects (a considerable lot of which are controlled by women's activist men's gatherings) to enable damaging men to bargain all the more viably with their brutality. Be that as it may, for brutal womenstrangely enoughno practically identical treatment programs exist. This reality further shows a significant issue: society is essentially unwillingor unableto recognize and manage rough ladies.

Why and How to Raise Your Self Esteem for Stress Relief

Why and How to Raise Your Self Esteem for Stress Relief Stress Management Management Techniques Print Raising Your Self Esteem for Stress Relief By Elizabeth Scott, MS twitter Elizabeth Scott, MS, is a wellness coach specializing in stress management and quality of life, and the author of 8 Keys to Stress Management. Learn about our editorial policy Elizabeth Scott, MS Updated on August 18, 2019 How Stress Impacts Your Health Overview Signs of Burnout Stress and Weight Gain Benefits of Exercise Stress Reduction Tips Self-Care Practices Mindful Living  Tim Robberts / Getty Images The way you feel about yourself, your self-esteem impacts your happiness level  and also can make life more or less stressful for you. For example, if you trust your ability to handle what comes, you will be more likely to see difficult situations as a challenge instead of as a threat; conversely, if you don’t trust your own ability to handle things, you will be more likely to see new situations as threatening and stress-provoking. Self-efficacy is the feeling that you are capable and resourceful, and this can contribute both to self-esteem and stress management. There are several things you can do to raise your self-esteem and self-efficacy that are also highly effective stress relievers. This can work in multiple ways to help you feel more in control of your life and build resilience.  It can also help you to enjoy your life more. If you feel that your self-esteem could use a boost, these are the activities to try. See what resonates with you, and give them a try. Work on Your Optimism If you are able to develop the ability to see the glass as half-full, this can contribute to feelings of self-efficacy as well as overall happiness and peace of mind.  Moreover, there are many proven benefits to optimism, so developing a greater sense of it, creating thinking habits that skew toward optimism, can provide these benefits for your health and general happiness.  Optimism involves more than simply looking on the bright side, however; it is a trait that can be developed by shifting your focus and self-talk, but there need to be specific ways in which you view the world.  Learn more about how to become an optimistic thinker. Develop Positive Self-Talk One thing that has a major influence on a person’s self-esteem is their self-talk, the way they talk to themselves, interpret things and comment on life inside their heads. A thinking style that is habitually negative can perpetuate a negative view of one’s life and self, as well as cause other problems. The following resources can help you to better understand your self-talk and alter it to a more positive way of thinking, helping you to see yourself and the world in a more positive way. Quiz: Are You An Optimist?Your thoughts color your world and your perception of yourself. Learn how positive or negative yours are!Negative Self Talk and StressSelf-talk is the internal dialogue we use to view the world, explain situations and communicate to ourselves, and the type of self-talk you useâ€"negative self-talk or positive self-talkâ€"can affect the level of stress you experience. Learn why, and find resources for change.Positive Self TalkNegative self-talk can limit you, increase your stress level, and adversely affect your self-concept. Here are some ways you can stop negative self-talk from damaging you, and reduce stress and improve your life by developing the habit of positive self-talk. Try New Challenges Even simply becoming immersed in hobbies can help with self-esteem  Learning what you are able to do well can provide you with a new view of yourself and a new level of self-respect.  Hobbies can also help you to relieve  stress, so hobbies can provide a double-win. Stay Away From Toxic People We can all feel negative from time to time, but some friends can tear you down instead of building you up, and those people can wear away at your self-esteem more than you may realize.  Learning to identify and create boundaries with those who drain us of our self-esteem can help.  Identifying and cultivating relationships with more supportive friends can build us up immensely as well. Help yourself cultivate the social life you deserve.

Machiavelli s The And Machiavellian Discourses - 1571 Words

The maintenance of a state requires the ability to act in accordance to the times. The Hobbesian and Machiavellian discourses in relation to the legitimacy of violence are distinct, nonetheless, bring forth significant arguments. Machiavelli claims that leaders ought to be good as long as the times permit, however, the leader with virtu ought to prepare to enter into evil when forced by necessity. Contrary to popular belief, Machiavelli does not endorse violence, rather he provides advice to those who wish to maintain their state or creation and in spite of the ravaging forces of time. The advice of Machiavelli is selective as it is geared to those who wish to maintain their state, not those preoccupied with salvation. In my understanding, Machiavelli advises that in order to maintain a political order, leaders ought to acquire virtu and not remain obstinate or operate with eternal principles. The Hobbesian account of the legitimacy of the use of violence is based on a notion of exc eptionalism, which is the distinctive characteristic of the sovereign. Whereas Machiavelli appeals to effects, Hobbes’ defence of the legitimacy of violence is intrinsically necessary to the notion of sovereignty. By definition, the sovereign is sovereign or exceptional to commit violence. For example, the governing laws of physics make it impossible for man to walk on water, except when the law-giver walks on water. It is in the nature of the sovereign to determine exceptions, any act ofShow MoreRelatedOrder In A Civic Society Is Kept By A Great Many Agents1733 Words   |  7 Pagesall the same? The political theorists Niccolà ² Machiavelli in The Discourses on Livy and Thomas Hobbes in Leviathan offer contrasting conclusions; the former believed obeying selfish motivation disastrous whereas the latter thought it fundamental towards maintaining the solvency of the country. The origin of their differing conclusions is found in their respective interpretations of the end a g overnment is meant to serve; to the republican Machiavelli, the government is a means to individual libertyRead MoreEssay about Machiavelli and War on Terror1100 Words   |  5 PagesIn both The Prince and The Discourses, Machiavelli presents very specific advice on how a ruler can maintain stability and control over his newly acquired state. Machiavelli lived in a time when a ruler could come to possess another kingdom through the simple act of war. Yet, in our modernity, a ruler cannot simply declare war and occupy a territory. He must also face repercussions from the other world powers that are in existence today. Our time has evolved and a ruler now has to take into considerationRead MorePower, Authority, and Accountability in Politics 1954 Words   |  8 Pagesvoting for them in the next election. (Hoffman, 2011) Niccolo Machiavelli is an important political theorist to look at while studying politics. Machiavelli was born in Florence, Italy on the Third of May 1469. Machiavelli was very interested in working in the field of politics. He held many political titles in his life. One such example is when he worked as an adviser to the Borgia family for political matters. [Wheeler, 2011] Machiavelli travelled all over Europe on diplomatic missions; here heRead More Machiavelli’s View of Human Nature Essay1696 Words   |  7 Pagessays â€Å"[they] will all think of their own interests †¦. for men will always be false †¦ unless they are compelled by necessity to be true.† (Prince, xxiii, p. 89) Beyond specific citations, there is what may be called the atmosphere of the work. Machiavelli constantly assumes that, regardless of what ought to be done, there is no reason to expect that it will be unless it accords with someone’s interests. Objectives which are not secular or this-worldly are only rarely mentioned, and those who concernRead MoreEssay about Machiavellis Reputation in the Modern World2985 Words   |  12 PagesMachiavellis Reputation in the Modern World Niccolà ² Machiavelli was known during much his life as a part of the republican government in Florence until 1512. At that time, the Medici family took over the city and ruled under a more monarchical system. From that point until his death in 1527, Machiavelli was always just on the outside of Florentine politics. He would occasionally get work from the Medici but his tasks were never as important as they had been under the republican governmentRead MoreSocrates And Niccolo Machiavelli1735 Words   |  7 PagesEssay 1: Socrates and Machiavelli Although Socrates and Niccolo Machiavelli lived in different time periods, the political climate that their philosophies were founded on were very similar. The trial of Socrates began after the Peloponnesian War when the new Spartan Tyranny took over the Athenian government. Socrates was accused of corrupting the youth and disrespecting the gods by the Spartan government. In the eyes of the Spartan government Socrates is a gadfly because of his posing of upsettingRead More Analysis of Mores The Prince and Utopia Essay1545 Words   |  7 Pageswith Raphael Nonsenso and his travels to Utopia. Niccolo Machiavelli was born in Florence, Italy in 1469 to a middleclass family. The time in which Machiavelli lived Italy as a country was not united but divide and split into little providences and republics. He latter became responsible for the Florentine militia against the Medici government and rule. When the Medici power reclaimed Florence Machiavelli was arrested for conspiracy he was tortured and then banished from FlorenceRead MoreNiccolo Machiavelli s The Prince1719 Words   |  7 PagesMachiavelli’s, The Prince, a book written by Niccolà ² Machiavelli, is a read that most people wouldn’t prefer to read as a first option but in defense to Niccolo, it brings out many themes such as Goodwill and Hatred, Free will, and Human Nature. â€Å"It is known from his personal correspondence that The Prince was written during 1513, the year after the Medici took control of Florence, and a few months after Machiavelli s arrest, torture, and banishment by the Medici regime† (Bio.com). The novel wasRead MoreOthello, By William Shakespeare1178 Words   |  5 Pagesrelationship also shares a distrust of their wives. The overall logical argument is based on love, jealousy and betrayal between two lovers that ultimately leads to their separation because of Iago’s evil plan. I am using this article to agree with Berry s view on how Iago separates two lovers just so he can take retaliation on Othello by manipulating everyone to unmasking their true intentions. He knows how to ask the right questions and say the right thing to achieve his desired consequence such as playactingRead MoreMachiavelli Essay1825 Words   |  8 PagesMachiavelli I would rather be in hell and converse with great minds than live in paradise with that dull rabble. In his lifes writings, Niccolo Machiavelli, sought out the strength of the human character, and wrote according to his own rules; trying to better the political philosophy of his time. Machiavelli, a fiercely independent Renaissance man, advocated the prosperity of Italian politics, and wanted Italy to rise above the rest of the world. Machiavellis writings dealt with many

Diversity, Inclusion And Social Justice - 845 Words

I find that the concepts of diversity, inclusion and social justice to be important because they build on each other and have the power to change the world. When all of these aspects work together and are acknowledged then we are able to work toward changing social norms and creating aspects in society that are focused on equity, rather than equality. Of course, social justice should be the goal that we as individuals want to achieve in liberating areas of our that have limited and restrained others. I connect diversity and appreciating diversity with being the foundation to this equation of equality because individuals need to understand that there will be differences between people. I enjoy the statement on, â€Å"†¦ Who is in the room?† because it starts to explain the variations in personal characteristics within a group of people. This is going to be part of my position as an RA within Resident Life because a floor’s residence are going to have wide range in t heir own diversities through their age, sexual orientation, journeys to get to college, race and ethnicity, etc. I am proud to have experienced the things I have and lived and go to high school in such a place like Aurora, CO to where I was able to live and embrace a diverse community. I came to define this diversity to be normal, but coming up to CSU and Fort Collins has shown me how much of Colorado does not have the same kind of standards. The next support beam to building this idea that works toward social would beShow MoreRelatedThe Gap Between Upper And Lower Class Essay1263 Words   |  6 Pagesbackgrounds (social justice). Social Justice and Inclusion We look at Social Justice and its’ effect on Students; are the areas where students born, nurtured and educated impacting their success in education and or in life? A basic understanding of Social Justice is â€Å"the fair and just relationship between an individual and society†, i.e equal rights and opportunities in all aspects. By putting motions in to place, such as inclusion, which is the educational response to issues of social justice, we canRead MoreDiversity And Cultural Diversity1198 Words   |  5 PagesAnaneh-Firempong (2003) cultural competence refers to understanding the importance of social and cultural influences that a minority group may have as an inherent trait. The authors also affirmed that a cultural competent system acknowledges, integrates and incorporates the relevance of culture, evaluation of cross-cultural relations, , and adaptation of services to meet culturally unique needs(pg.294). Diversity and cultural competence are two main concepts that are essential to address and takeRead MoreSustainable Development and Businesses Essay1049 Words   |  5 Pagesenvironmental, social, and economical issues have arisen in society and businesses. Only recently has the issues established extensive attention within society, sustainable development is acknowledged by the majority to mean ‘development that meets the needs of the present without compromising the ability of future generations to meet their own needs’ (Commission 1987). This essay will look into the practices of ANZ as a sustainable business and examine their ecological, economic and social environmentsRead More The Importance of Inclusive Education in Australia Essay808 Words   |  4 Pagesfamous quote by an unknown author about celebrating individual differences. Difference is defined by Ashman and Elkins; as varying levels of social, emotional, physical and intellectual qualities that make us a ll different from other people (Ashman Elkins, 2009). In today’s world this is viewed as society’s version of normality (Ashman Elkins, 2009). Inclusion involves the incorporation of all types of differences into a mainstream classroom (Ashman Elkins, 2009). It is unfortunate that evenRead MoreIntroduction. The Pateman Vincent Statement From 20101486 Words   |  6 Pagespublic libraries and by the profession to combat social exclusion and promote social justice and suggest how the profession can carve out a new direction for itself in a world where the use of traditional library services in decline. Discussion After conducting a review of literature, Levitas et al (2007) concluded in their report for the government’s social exclusion task force that a suitable definition for social exclusion should be: ‘Social exclusion is a complex and multidimensional processRead MoreCorporate Social Responsibility At The Bank Of America Corporation1544 Words   |  7 PagesCorporate Social Responsibility at the Bank of America Corporation Overview of Corporate Social Responsibility the Bank of America Corporation Background Information About Bank of America The Bank of America Corporation (Bank of America) is a bank and financial holding company that serves â€Å"individual consumers, small- and middle-market businesses, institutional investors, corporations and Governments with†¦ bank and nonbank financial services and products.† (Reuters) Profiting $5.32 billion inRead MoreEqual Pay Act 1970 : Equality And Diversity963 Words   |  4 PagesEquality To me this means treating everyone with respect and fairness whilst recognising their individual needs. Diversity Recognising, valuing and acknowledging difference and similarity. Inclusion Providing opportunities to everyone, in its simplest term it is the ‘state of being included’. The Equality act 2010 replaced nine primary legislations and over 100 bits of secondary legislation to make it simpler to understand and ensure that everyone is treated fairly and brings together a numberRead MoreThe American Association Of Intellectual And Developmental Disabilities Essay1386 Words   |  6 Pagesdisabilities may be restricted from participating in events in society because of their functional disabilities. Environmental and personal factors also play a role in affecting people’s lives (CDC, 2014). According to the U.S. Department of Justice (2009): An individual with a disability is defined by the American with Disabilities Act (ADA) as a person who has a physical or mental impairment that substantially limits one or more major life activities, a person who has a history or record ofRead MoreWhy A Diverse Workplace Matters?1093 Words   |  5 Pagesfor the success of an organization. Diversity means differences due to race, gender, ethnic groups, age, personality, tenure, organizational function, educational background, etc. Diversity involves how people perceive themselves and how they perceive others. These perceptions affect their interactions. Why a diverse workplace matters? / Benefits of workplace diversity An organization’s success and competitiveness depends upon it’s ability to embrace diversity and realize it’s benefits. Due to diversRead MoreMy Experience As A Primary Teacher839 Words   |  4 PagesI need to include all the students with diverse abilities and to meet their learning needs. At the beginning, I found it challenging to practice the inclusive education strategy in my classroom, so I started to read more about the definition of inclusion and the factors that affect the teachers’ practical experience. Later, I was inspired by the relation between the inclusive education and the Australian Curriculum. The Australian Curriculum establishes expectations which are appropriate for all

Tkam Theme Essay Free Essays

Kiah Lyons Mrs. Farrands Honors English II 30 October 2012 As children, we are taught simply that something whether it is a person, object, or belief is simply good or bad. We can classify or identify what is good or bad using three sources. We will write a custom essay sample on Tkam Theme Essay or any similar topic only for you Order Now Typically our beliefs are primarily based on what our household says. Society also has a large role in our views as well. If something is illegal, outlawed, or even frowned upon by society it is considered bad. However, saying something is acceptable or not acceptable is something completely different from what our actions say. Many parents use the saying: Do as I say, not as I do. Sometimes we know something goes against what is right or against or morals but we do it regardless. Scout sees that in most instances; what those in her household tell her, what society tells her, and what her family and society does do not all coincide. This is evident when analyzing two main topics of the book which are race and Boo Radley. Atticus always tells Scout and Jem the importance of treating colored people equally if not better. While talking to Mr. Raymond, Scout tells him that Atticus told her â€Å"cheatin’ a colored man is ten times worse than cheatin’ a white man, Says it’s the worst thing you can do† (Lee 205). While defending Tom Robinson, Atticus told the court: â€Å"The truth is this: some Negroes lie, some Negroes are immoral, some Negro men are not to be trusted around women-black or white. But this is a truth that applies to the human race and to no particular race of men† showing his strong belief of equality among all men no matter what their skin color may be (Lee 208). Even though Atticus strongly believes in the quote from Thomas Jefferson that â€Å"All men are created equal†, Aunt Alexandra tended to have a different perspective regarding colored men and women (Lee 208). This is strongly evident in the way she treats and talks about Calpurnia. When Aunt Alexandra first arrived, instead of a cordial greeting she tells Calpurnia right away â€Å"Put my bag in the front bedroom, Calpurnia† which shows that Aunt Alexandra views Calpurnia of a different class and has no respect for her. Aunt Alexandra disapproved of practically everything that Calpurnia did, and if it could be avoided, she did not want Scout and Jem spending any extra time with her. Although Scout looks forward to going to Calpurnia, Aunt Alexandra is not fond of the idea, and actually encourages Atticus to fire Cal. She believes Cal is not a good role mole which leads her to tell Atticus to â€Å"face it sooner or later [†¦] We don’t need her now† (Lee 138). Aunt Alexandra felt that just because Calpurnia was black, she was not suited as a mother figure, and allowed her assumptions about blacks affect her view of Calpurnia. Throughout the summer, Jem, Scout, and Dill love to reenact Boo Radley’s life and play games which include messing with the house, which Atticus does not approve of. When he caught the kids he told them that â€Å"what Mr. Radley did was his own business. If he wanted to come out, he would† (Lee 50). Although the rest of his family may not have the same beliefs as Atticus, he takes highly his standards and morals of treating men of all types and colors with respect and equality. It is clear that Maycomb’s society does not agree with Atticus defending Tom Robinson. Scout does not realize that she would face this opposition until a few members of Maycomb make remarks about Atticus to her, not having the guts to say anything to Atticus’ face. In school, Scout faces her first opposition from Cecil Jacobs when he says: â€Å"Scout Finch’s daddy defended niggers† (Lee 77). Even some of her family disapproves of Atticus defending Tom. Francis, only repeating what his grandmother says, tells Scout that Atticus â€Å"is a nigger-lover† and â€Å"we’ll never be able to walk the streets of Maycomb agin. He’s ruinin’ the family†, which of course leads to Scout punching Francis (Lee 85-87). Passing by Mrs. Dubose, Scout and Jem get more of the usual harassment when she says makes a condescending remark about a Finch â€Å"in the courthouse lawing for niggers† and that Atticus is â€Å"no better than the niggers and trash he works for† (Lee 105). As for Boo Radley, most everyone in Maycomb has a different story for Boo Radley and why he stays at home all day. Stephanie Crawford even claims â€Å"she woke up in the middle of the night one time and saw him looking straight through the window at her† (Lee 13). Jem said that Boo â€Å"dined on raw squirrels and any cats he could catch, [†¦] his eyes popped, and he drooled most of the time†, obviously a tale but no one said anything different. (Lee 13). It would be easy for Scout to fall in line with what the majority of what people think so that she would be accepted. The characters’ actions throughout the book show if they actually live by what they preach. For example, Atticus knows that he will face disapproval defending Tom Robinson. He tells Jack that â€Å"reasonable people go stark raving mad when anything involving a Negro comes up† (Lee 91). Knowing that he cannot go against what he believes, he defends Tom despite the opposition. He also defends Calpurnia when Aunt Alexandra talks negatively about her saying â€Å"Calpurnia is not leaving this house until she wants to. You may think otherwise, but I couldn’t have got along without her all these years. She’s a faithful member of this family and you’ll simply have to accept things the way they are† later adding â€Å"She tried to bring them up according to her lights, and Cal’s lights are pretty good ? and another thing, the children love her† (Lee 138). Atticus could have easily taken his sister’s side, but he really appreciates everything that Cal has done for his family. Society believes that black people are of a lesser class which is the focal point of the Tom Robinson case. Even though Tom had more evidence to prove him innocent than the plaintiff had to prove him guilty, his race was what ultimately convicted Tom. Atticus makes the statement in front of the court that the â€Å"case is not a difficult one [†¦] It should have never come to trial. This case is as simple as black and white† (Lee 207). Regarding Boo Radley, no one attempts to make an effort to stand up against the unruly rumors such as that Boo â€Å" went out at night when the moon was down, and peeped in windows. When people’s azaleas froze in a cold snap, it was because he had breathed on them. † and the â€Å"Radley pecans would kill you† (Lee 9). It was more important to have a good story, than to have the not-so lively truth. Their actions showed their true beliefs. We can be molded into good people by taking the good and bad from each source, or we can be brainwashed into one source. Each source has their pros and cons, which is why it is important to take what people say with a grain of salt, before immediately adapting their views. Regardless, we can all learn things from our household’s beliefs, what society says, and what peoples’ actions say. As we grow as a people and we gain experience, we gain a better understanding of what is good and bad, right and wrong. How to cite Tkam Theme Essay, Essay examples

Math 533 Essay Example

Math 533 Essay 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Team League (American 1, National 0) Built (Year Stadium Was Built) Size (Stadium Capacity) Salary (Total 2000 Team Salary $ Mil) Attendance (Total 2000 Team Attendance) Wins (Number of Wins in 2000) ERA (Earned Run Average) Batting (Team Batting Average) HR (Number of Home Runs for the Team) Surface (Natural 0, Artificial 1) Stolen (Stolen Bases) Errors (Team Errors) Year Average (Average Player Salary) Median (Median Player Salary) x1 Team Boston New York Yankees Oakland Baltimore Anaheim Cleveland Chicago Toronto Minnesota Tampa Bay Texas Detroit Seattle Kansas City Atlanta Arizona Houston Cincinnati New York Mets Pittsburgh Los Angeles San Diego Montreal San Francisco St. Louis Florida Philadelphia Milwaukee Chicago Cubs Colorado x2 League 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 x3 Built 1912 1923 1966 1992 1966 1994 1991 1989 1982 1990 1994 2000 1999 1973 1993 1998 2000 1970 1964 1970 1962 1967 1976 1900 1966 1987 1971 1953 1914 1995 x4 Size 33,871 57,746 43,662 48,262 45,050 43,368 44,321 50,516 48,678 44,027 52,000 40,000 45,611 40,529 50,062 49,075 42,000 52,953 55,775 47,972 56,000 53,166 46,500 40,800 49,625 42,531 62,411 43,000 38,957 50,381 x5 Salary 93. 9 113. 4 33. 0 59. 2 58. 7 78. 7 36. 9 54. 6 15. 8 55. 2 61. 4 60. 6 62. 6 24. 5 95. 0 80. 8 52. 0 35. 1 89. 7 31. 9 94. 2 54. 7 28. 0 54. 2 72. 4 25. 9 36. 7 33. 8 51. 1 56. 0 x6 Attendance 2,585,895 3,227,657 1,728,885 3,297,031 2,066,982 3,456,278 1,947,799 1,819,919 1,059,415 1,479,782 2,800,075 2,533,753 3,148,317 1,677,915 3,234,304 2,819,539 3,056,139 2,577,371 2,820,530 1,748,908 3,011,539 2,423,149 926,272 3,318,800 3,336,493 1,218,326 1,612,769 1,573,621 2,789,511 3,295,129 x7 Wins 85 87 91 74 82 90 95 83 69 69 71 79 91 77 95 85 72 85 94 69 86 76 67 97 95 79 65 73 65 82 Tables and Data Sets 267 Appendix D Data Set 2 — Major League Baseball (continued) x1 Row 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 x7 Wins 5 87 91 74 82 90 95 83 69 69 71 79 91 77 95 85 72 85 94 69 86 76 67 97 95 79 65 73 65 82 x8 ERA 4. 23 4. 76 4. 58 5. 37 5. 00 4. 84 4. 66 5. 14 5. 14 4. 86 5. 52 4. 71 4. 49 5. 48 4. 05 4. 35 5. 42 4. 33 4. 16 4. 94 4. 10 4. 52 5. 13 4. 21 4. 38 4. 59 4. 77 4. 63 5. 25 5. 26 x9 Batting 0. 267 0. 277 0. 270 0. 272 0. 280 0. 288 0. 286 0. 275 0. 270 0. 257 0. 283 0. 275 0. 269 0. 288 0. 271 0. 265 0. 278 0. 274 0. 263 0. 267 0. 257 0. 254 0. 266 0. 278 0. 270 0. 262 0. 251 0. 246 0. 256 0. 294 x10 HR 167 205 239 184 236 221 216 244 116 162 173 177 198 150 179 179 249 200 198 168 211 157 178 226 235 160 144 177 183 161 11 Surface 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 1 0 0 0 x12 Stolen 318 182 184 208 202 218 158 198 128 228 130 110 164 236 198 204 222 162 266 202 212 212 246 194 138 208 154 172 188 204 x13 Errors 109 109 134 116 134 72 133 100 102 118 135 105 99 102 129 107 133 111 118 132 135 141 132 93 111 125 100 118 100 94 Team Boston New York Yankees Oakland Baltimore Anaheim Cleveland Chicago Toronto Minnesota Tampa Bay Texas Detroit Seattle Kansas City Atlanta Arizona Houston Cincinnati New York Mets Pittsburgh Los Angeles San Diego Montreal San Francisco St. We will write a custom essay sample on Math 533 specifically for you for only $16.38 $13.9/page Order now We will write a custom essay sample on Math 533 specifically for you FOR ONLY $16.38 $13.9/page Hire Writer We will write a custom essay sample on Math 533 specifically for you FOR ONLY $16.38 $13.9/page Hire Writer Louis Florida Philadelphia Milwaukee Chicago Cubs Colorado 268 Appendixes Appendix D Data Set 2 — Major League Baseball (concluded) x14 Row 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Year 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 x15 Average 52,300 74,000 97,800 121,900 146,500 196,500 245,000 289,000 325,900 368,998 410,517 402,579 430,688 489,539 589,483 845,383 1,012,424 1,062,780 1,154,486 1,094,440 1,101,455 1,314,420 1,384,530 1,567,873 1,983,849 16 Median * * * * * * * 207,500 229,750 265,833 275,000 235,000 235,000 280,000 350,000 412,000 392,500 371,500 450,000 275,000 300,000 400,000 427,500 495,000 700,000 Tables and Data Sets 269 Appendix E Data Set 3 — OECD x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x1 Australia Austria Belgium Canada Czech Republic Denmark Finland France Germany Greece Hungary Iceland Ireland Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Spain Sweden Switzerland Turkey United Kingdom United States Country G7 Member (1 Yes, 0 No) Total area of country in thousand square kilometers Population in thousands Percent of population over 65 years of age Exchange rate per U. S. dollar Gross Domestic Product at current exchange rate in billions of dollars Energy use in millions of tons of oil equivalent Index of total manufacturing (1900 Total labor force in thousands Region (1 x2 0 0 0 1 0 0 0 1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 100) Far East, 2 x3 7,687 84 31 9,976 79 43 338 549 357 132 93 103 70 301 378 98 3 1,973 41 269 324 313 92 505 450 41 781 245 9,373 Europe, 3 x5 12. 1 15 16. 1 12. 2 13. 4 15. 1 14. 4 15. 15. 8 15. 8 14. 2 11. 4 11. 5 15. 8 14. 5 6. 1 14. 2 4. 8 13. 3 11. 6 15. 9 11. 3 14. 8 15. 6 17. 3 14. 9 4. 8 15. 7 12. 8 North America) x6 x7 390. 9 228. 7 268. 2 579. 2 56. 2 174. 9 125. 1 1,536. 6 235. 35 122. 4 44 7. 3 70. 7 1,243. 2 4,595. 2 484. 8 17 329. 4 396 65. 9 157. 8 134. 4 103. 6 584. 9 251. 7 294. 3 181. 5 1,153. 4 7,388. 1 x4 18,289 8,060 10,157 29,964 10,316 5,262 5,125 58,380 81,87 7 10,465 10,193 270 3,621 57,473 125,864 45,545 418 96,582 15,494 3,640 4,370 38,618 9,935 39,270 8,901 7,085 62,695 58,782 265,557 x8 100. 61 27. 19 56. 4 236. 17 40. 4 22. 87 31. 48 254. 349. 55 24. 39 25. 47 2. 27 11. 96 161. 14 510. 36 162. 87 3. 45 141. 38 75. 8 16. 3 23. 15 108. 41 19. 15 101. 41 52. 57 25. 62 65. 52 234. 72 2,134. 96 x9 109 111 108 112 117 121 98 97 98 x10 9,184 3,876 4,297 15,209 5,175 2,822 2,531 25,613 39,294 4,249 4,048 148 1,494 23,385 67,110 21,188 218 34,325 7,516 1,797 2,246 17,203 4,885 16,159 4,310 3,967 22,736 28,552 135,231 x11 1 2 2 3 2 2 2 2 2 2 2 2 2 2 1 1 2 3 2 1 2 2 2 2 2 2 2 2 3 1. 509 12. 51 36. 61 1. 426 34. 73 6. 771 5. 369 5. 955 1. 777 279. 6 201. 3 71. 71 0. 687 1743 129. 4 1477 8. 123 2. 004 1. 689 7. 25 3. 532 181. 5 150. 7. 785 1. 44 199,026 0. 603 1 175 104 98 163 100 118 109 119 115 97 103 121 103 129 102 118 270 Appendixes Appendix F Data Set 4 — Northwest Ohio School Districts x1 x2 x3 x4 x5 x6 x7 x8 x9 x1 Bluffton Shawne e Spencerville Delphos Elida Lima Northeastern Ayersville Defiance Hicksville Central Berlin-Milan Perkins Huron Margaretta Sandusky Kelleys Island Pettisville Wauseon Evergreen Archbold-Area Pike-Delta-York Gorham-Fayette Swanton Arlington Vanlue Liberty-Benton Van Buren Cory-Rawson Arcadia McComb Findlay Ada Kenton Liberty Center Patrick Henry Napoleon Area Holgate Monroeville Name of district Number of students Mean family income in the district ($) Mean property value in the district ($) Percent of families receiving welfare Mean salary of classroom teachers ($) Amount spent per pupil ($) Mean daily attendance Percent passing 12th grade proficiency exam x2 1,132 2,472 1,026 1,104 3,204 5,963 1,194 921 3,046 990 1,216 1,593 2,038 1,494 1,560 4,426 20 503 1,864 1,238 1,401 1,559 487 1,725 685 346 954 840 794 597 805 5,758 855 2,228 1,009 1,176 2,331 605 686 x3 4,487 29,777 23,161 21,792 24,446 18,394 26,428 28,228 23,812 22,448 24,189 25,223 25,586 27,135 23,849 19,529 19,854 25,079 23,408 23,826 26,706 23,396 22,405 24,596 26,175 24,709 28,718 28,964 23,904 24,305 23,754 24,269 23,029 20,418 24,723 23,061 25,304 23,962 22,942 x4 62,678 130,910 51,645 88,453 65,550 44,138 88,789 82,707 56,333 56,411 53,923 76,878 117,545 105,588 74,601 72,425 802,081 53,948 60,896 69,432 107,547 48,638 57,221 69,320 55,478 49,606 77,503 151,992 69,242 78,102 69,347 92,648 52,655 61,155 57,685 63,134 84,245 49,709 63,103 5 1. 8 2. 6 5. 4 6. 2 8. 9 33. 8 1. 7 3. 9 11. 2 7 4. 6 4 3. 3 4. 6 2. 8 25. 2 11. 4 3. 9 4. 9 5. 2 4. 1 6. 1 6. 9 6. 3 2. 7 4. 1 1. 5 1. 8 2. 4 2. 5 5. 7 7. 6 5. 3 13. 8 4. 1 5. 2 6. 6 6 4. 3 x6 31,221 34,860 30,155 32,273 32,876 33,142 30,919 32,850 34,750 34,224 34,430 32,166 39,352 33,433 37,084 36,042 27,144 31,159 32,499 32,353 35,982 31,310 33,166 33,690 31,821 28,411 30,330 33,447 31,241 30,738 28,986 35,879 28,479 30,907 30,904 31,895 32,773 31,324 30,838 x7 ,130 2,570 2,262 2,506 2,250 2,657 2,431 2,693 2,438 2,351 2,496 2,564 2,861 2,968 2,464 2,766 11,226 2,834 2,252 2,250 2,837 2,309 2,492 2,615 2,205 2,420 2,063 2,584 2,416 2,752 2,321 2,860 2,380 2,512 2,431 2,552 2,422 2,454 2,474 x8 95. 7 94. 7 95. 5 96. 5 94. 1 92. 3 96. 1 95. 6 94. 2 95. 7 94. 8 96. 1 95. 8 95. 4 95. 5 93 95 96. 1 95. 3 95 96. 2 94. 8 94. 6 94. 9 96. 5 96. 2 96. 7 96. 4 96. 4 95. 9 95. 9 94. 9 95. 9 93. 7 95. 8 95. 9 94. 6 94. 9 95. 8 x9 85 73 68 65 62 40 72 68 63 59 56 77 74 74 66 37 100 78 75 72 69 66 51 50 84 83 78 75 73 64 61 60 69 54 82 75 73 71 64 Tables and Data Sets 271 Appendix F Data Set 4 — Northwest Ohio School Districts (concluded) x1 Bellevue Willard Norwalk Ottawa Hills Anthony Wayne Sylvania Maumee Oregon Washington Springfield Toledo Benton Carroll Salem Danbury Genoa Port Clinton Put-in-Bay Paulding Ottoville Columbus Grove Kalida Continental Ottawa-Glandorf Pandora-Gilboa Leipsic Gibsonburg Lakota Fremont Woodmore Clyde–Green Springs Bettsville Seneca East Old Fort Hopewell-Loudon New Riegel Tiffin Fostoria Van Wert Edon-Northwest Milcreek–West Unity Bryan North Central Montpelier Edgerton Stryker Perrysburg Elmwood Bowling Green Otsego Northwood Eastwood Lake Rossford North Baltimore Upper Sandusky Carey 2 2,276 2,300 2,650 933 3,178 7,822 3,009 3,594 7,154 3,575 36,790 2,063 635 1,584 2,238 70 1,993 610 866 775 792 1,749 632 748 983 1,332 5,156 1,141 2,368 347 1,183 540 870 459 3,632 2,742 2,504 744 788 2,266 757 1,172 767 579 3,839 1,237 3,534 1,643 1,091 1,739 1,665 2,087 839 1,801 915 x3 4,025 23,304 21,551 45,723 29,215 32 ,114 27,604 24,525 23,507 26,048 21,079 23,899 21,325 25,321 20,941 19,266 22,677 24,128 23,562 24,456 23,625 25,363 23,806 20,941 23,312 22,678 22,327 26,460 23,854 22,103 22,656 23,208 22,103 23,314 21,246 20,809 22,728 23,035 21,302 22,607 21,871 20,787 22,429 24,084 32,773 22,179 21,307 24,614 25,905 25,043 23,559 25,360 22,075 21,063 21,658 x4 6,912 58,832 72,266 122,356 88,004 101,503 117,921 123,599 102,485 98,346 62,668 237,206 182,360 53,120 129,961 426,419 46,163 46,582 55,568 44,267 37,277 64,288 55,446 62,648 46,098 55,933 74,874 90,484 55,724 37,269 50,895 50,712 72,201 41,376 65,291 62,268 67,932 38,462 40,239 81,152 59,396 44,383 54,040 65,532 97,888 47,644 84,682 57,601 77,077 67,929 95,859 123,725 58,383 68,348 51,497 x5 6. 9 14. 3 12. 2 0. 2 3. 1 3. 8 3. 9 8. 7 11. 8 12. 2 42. 8 4. 7 3. 2 4. 8 10. 5 1. 4 8. 6 0. 2 8. 4 0. 7 10 6. 5 1. 2 16. 1 17. 8 10. 16. 2 10. 9 7 6. 1 4. 8 19. 3 4. 7 2. 7 9 20. 4 7. 1 2. 7 3. 2 4. 2 2. 9 8. 2 4. 1 3. 4 2. 6 7. 5 7. 5 5 7. 9 4. 7 6. 2 7. 2 10. 6 3. 9 6 x6 32,164 35,042 37,145 43,256 35,617 39,684 41,634 35,848 39,155 34,437 36,190 42,734 34,971 34,661 39,542 30,242 32,928 26,125 30,476 28,962 28,945 31,185 27,693 30,282 31,244 30,765 37,759 32,296 33,998 27,466 29,940 28,195 30,644 29,099 35,513 34,241 33,885 30,833 31,582 32,643 31,978 33,243 28,975 33,855 40,320 30,434 37,983 36,065 35,536 35,742 38,046 39,476 29,579 32,778 30,968 x7 ,374 2,347 2,384 4,150 2,844 2,943 3,933 2,941 2,997 2,774 2,611 3,444 3,158 2,845 2,926 7,824 2,560 2,588 2,174 2,274 2,225 2,154 2,078 2,811 2,242 2,306 2,616 2,227 2,383 2,394 2,435 2,743 2,564 2,501 2,506 2,455 2,511 1,916 2,382 2,706 2,349 2,654 2,470 2,617 3,011 2,643 2,849 2,539 2,979 2,499 2,820 3,258 2,331 2,267 2,513 x8 95. 1 94. 6 94 95. 7 95. 3 95. 5 95 94. 7 93. 7 93. 8 90. 7 95. 6 95. 3 95. 9 94. 5 94. 5 94. 5 99. 8 96. 2 96. 8 95. 5 96. 5 96. 5 93. 9 94. 4 95. 2 94. 7 96. 5 94. 6 95. 8 95. 9 96 94. 6 97 94. 7 92. 7 95. 3 95. 1 95. 9 95. 2 95. 6 94. 8 95. 9 95. 7 96. 1 95. 2 94. 7 95. 4 94. 9 95. 9 95. 2 94. 9 94. 5 95. 95. 5 x9 55 53 50 95 75 72 69 52 51 49 28 81 65 65 50 33 59 86 84 81 79 77 67 47 71 66 57 56 47 83 80 78 74 73 67 34 61 73 71 69 68 67 61 47 98 68 68 64 61 60 55 54 50 62 59 272 Appendixes Appendix G Critical Values of the F Distribution at a 5 Percent Level of Significance . 05 0 F Degrees of Freedom for the Numerator 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 30 40 60 120 161 18. 5 10. 1 7. 71 6. 61 5. 99 5. 59 5. 32 5. 12 4. 96 4. 84 4. 75 4. 67 4. 60 4. 54 4. 49 4. 45 4. 41 4. 38 4. 35 4. 32 4. 30 4. 28 4. 26 4. 24 4. 17 4. 08 4. 00 3. 92 3. 84 2 200 19. 0 9. 55 6. 94 5. 79 5. 14 4. 74 4. 46 4. 26 4. 0 3. 98 3. 89 3. 81 3. 74 3. 68 3. 63 3. 59 3. 55 3. 52 3. 49 3. 47 3. 44 3. 42 3. 40 3. 39 3. 32 3. 23 3. 15 3. 07 3. 00 3 216 19. 2 9. 28 6. 59 5. 41 4. 76 4. 35 4. 07 3. 86 3. 71 3. 59 3. 49 3. 41 3. 34 3. 29 3. 24 3. 20 3. 16 3. 13 3. 10 3. 07 3. 05 3. 03 3. 01 2. 99 2. 92 2. 84 2. 76 2. 68 2. 6 0 4 225 19. 2 9. 12 6. 39 5. 19 4. 53 4. 12 3. 84 3. 63 3. 48 3. 36 3. 26 3. 18 3. 11 3. 06 3. 01 2. 96 2. 93 2. 90 2. 87 2. 84 2. 82 2. 80 2. 78 2. 76 2. 69 2. 61 2. 53 2. 45 2. 37 5 230 19. 3 9. 01 6. 26 5. 05 4. 39 3. 97 3. 69 3. 48 3. 33 3. 20 3. 11 3. 03 2. 96 2. 90 2. 85 2. 81 2. 77 2. 74 2. 71 2. 68 2. 66 2. 64 2. 62 2. 60 2. 53 2. 5 2. 37 2. 29 2. 21 6 234 19. 3 8. 94 6. 16 4. 95 4. 28 3. 87 3. 58 3. 37 3. 22 3. 09 3. 00 2. 92 2. 85 2. 79 2. 74 2. 70 2. 66 2. 63 2. 60 2. 57 2. 55 2. 53 2. 51 2. 49 2. 42 2. 34 2. 25 2. 18 2. 10 7 237 19. 4 8. 89 6. 09 4. 88 4. 21 3. 79 3. 50 3. 29 3. 14 3. 01 2. 91 2. 83 2. 76 2. 71 2. 66 2. 61 2. 58 2. 54 2. 51 2. 49 2. 46 2. 44 2. 42 2. 40 2. 33 2. 25 2. 17 2. 09 2. 01 8 239 19. 4 8. 85 6. 04 4. 82 4. 15 3. 73 3. 44 3. 23 3. 07 2. 95 2. 85 2. 77 2. 70 2. 64 2. 59 2. 55 2. 51 2. 48 2. 45 2. 42 2. 40 2. 37 2. 36 2. 34 2. 27 2. 18 2. 10 2. 02 1. 94 9 241 19. 4 8. 81 6. 00 4. 77 4. 10 3. 68 3. 39 3. 18 3. 02 2. 90 2. 80 2. 71 2. 5 2. 59 2. 54 2 . 49 2. 46 2. 42 2. 39 2. 37 2. 34 2. 32 2. 30 2. 28 2. 21 2. 12 2. 04 1. 96 1. 88 10 242 19. 4 8. 79 5. 96 4. 74 4. 06 3. 64 3. 35 3. 14 2. 98 2. 85 2. 75 2. 67 2. 60 2. 54 2. 49 2. 45 2. 41 2. 38 2. 35 2. 32 2. 30 2. 27 2. 25 2. 24 2. 16 2. 08 1. 99 1. 91 1. 83 12 244 19. 4 8. 74 5. 91 4. 68 4. 00 3. 57 3. 28 3. 07 2. 91 2. 79 2. 69 2. 60 2. 53 2. 48 2. 42 2. 38 2. 34 2. 31 2. 28 2. 25 2. 23 2. 20 2. 18 2. 16 2. 09 2. 00 1. 92 1. 83 1. 75 15 246 19. 4 8. 70 5. 86 4. 62 3. 94 3. 51 3. 22 3. 01 2. 85 2. 72 2. 62 2. 53 2. 46 2. 40 2. 35 2. 31 2. 27 2. 23 2. 20 2. 18 2. 15 2. 13 2. 11 2. 09 2. 01 1. 92 1. 84 1. 75 1. 7 20 248 19. 4 8. 66 5. 80 4. 56 3. 87 3. 44 3. 15 2. 94 2. 77 2. 65 2. 54 2. 46 2. 39 2. 33 2. 28 2. 23 2. 19 2. 16 2. 12 2. 10 2. 07 2. 05 2. 03 2. 01 1. 93 1. 84 1. 75 1. 66 1. 57 24 249 19. 5 8. 64 5. 77 4. 53 3. 84 3. 41 3. 12 2. 90 2. 74 2. 61 2. 51 2. 42 2. 35 2. 29 2. 24 2. 19 2. 15 2. 11 2. 08 2. 05 2. 03 2. 01 1. 98 1. 96 1. 89 1. 79 1. 70 1. 61 1. 52 30 250 19. 5 8. 62 5. 75 4. 50 3. 81 3. 38 3. 08 2. 86 2. 70 2. 57 2. 47 2. 38 2. 31 2. 25 2. 19 2. 15 2. 11 2. 07 2. 04 2. 01 1. 98 1. 96 1. 94 1. 92 1. 84 1. 74 1. 65 1. 55 1. 46 40 251 19. 5 8. 59 5. 72 4. 46 3. 77 3. 34 3. 04 2. 83 2. 66 2. 53 2. 43 2. 34 2. 27 2. 20 2. 5 2. 10 2. 06 2. 03 1. 99 1. 96 1. 94 1. 91 1. 89 1. 87 1. 79 1. 69 1. 59 1. 50 1. 39 Degrees of Freedom for the Denominator Tables and Data Sets 273 Appendix G Critical Values of the F Distribution at a 1 Percent Level of Significance . 01 0 F Degrees of Freedom for the Numerator 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 30 40 60 120 4052 98. 5 34. 1 21. 2 16. 3 13. 7 12. 2 11. 3 10. 6 10. 0 9. 65 9. 33 9. 07 8. 86 8. 68 8. 53 8. 40 8. 29 8. 18 8. 10 8. 02 7. 95 7. 88 7. 82 7. 77 7. 56 7. 31 7. 08 6. 85 6. 63 2 5000 99. 0 30. 8 18. 0 13. 3 10. 9 9. 55 8. 65 8. 02 7. 56 7. 21 6. 93 6. 70 6. 51 6. 36 6. 3 6. 11 6. 01 5. 93 5. 85 5. 78 5. 72 5. 66 5. 61 5. 57 5. 39 5. 18 4. 98 4. 79 4. 61 3 5403 99. 2 29. 5 16. 7 12. 1 9. 78 8. 45 7. 59 6. 99 6. 55 6. 22 5. 95 5. 74 5. 56 5. 42 5. 29 5. 18 5. 09 5. 01 4. 94 4. 87 4. 82 4. 76 4. 72 4. 68 4. 51 4. 31 4. 13 3. 95 3. 78 4 5625 99. 2 28. 7 16. 0 11. 4 9. 15 7. 85 7. 01 6. 42 5. 99 5. 67 5. 41 5. 21 5. 04 4. 89 4. 77 4. 67 4. 58 4. 50 4. 43 4. 37 4. 31 4. 26 4. 22 4. 18 4. 02 3. 83 3. 65 3. 48 3. 32 5 5764 99. 3 28. 2 15. 5 11. 0 8. 75 7. 46 6. 63 6. 06 5. 64 5. 32 5. 06 4. 86 4. 69 4. 56 4. 44 4. 34 4. 25 4. 17 4. 10 4. 04 3. 99 3. 94 3. 90 3. 85 3. 70 3. 51 3. 34 3. 17 3. 02 6 5859 99. 27. 9 15. 2 10. 7 8. 47 7. 19 6. 37 5. 80 5. 39 5. 07 4. 82 4. 62 4. 46 4. 32 4. 20 4. 10 4. 01 3. 94 3. 87 3. 81 3. 76 3. 71 3. 67 3. 63 3. 47 3. 29 3. 12 2. 96 2. 80 7 5928 99. 4 27. 7 15. 0 10. 5 8. 26 6. 99 6. 18 5. 61 5. 20 4. 89 4. 64 4. 44 4. 28 4. 14 4. 03 3. 93 3. 84 3. 77 3. 70 3. 64 3. 59 3. 54 3. 50 3. 46 3. 30 3. 12 2. 95 2. 79 2. 64 8 5981 99. 4 27. 5 14. 8 10. 3 8. 10 6. 84 6. 03 5. 47 5. 06 4. 74 4. 50 4. 30 4. 14 4. 00 3. 89 3. 79 3 . 71 3. 63 3. 56 3. 51 3. 45 3. 41 3. 36 3. 32 3. 17 2. 99 2. 82 2. 66 2. 51 9 6022 99. 4 27. 3 14. 7 10. 2 7. 98 6. 72 5. 91 5. 35 4. 94 4. 63 4. 39 4. 19 4. 03 3. 89 3. 78 3. 68 3. 0 3. 52 3. 46 3. 40 3. 35 3. 30 3. 26 3. 22 3. 07 2. 89 2. 72 2. 56 2. 41 10 6056 99. 4 27. 2 14. 5 10. 1 7. 87 6. 62 5. 81 5. 26 4. 85 4. 54 4. 30 4. 10 3. 94 3. 80 3. 69 3. 59 3. 51 3. 43 3. 37 3. 31 3. 26 3. 21 3. 17 3. 13 2. 98 2. 80 2. 63 2. 47 2. 32 12 6106 99. 4 27. 1 14. 4 9. 89 7. 72 6. 47 5. 67 5. 11 4. 71 4. 40 4. 16 3. 96 3. 80 3. 67 3. 55 3. 46 3. 37 3. 30 3. 23 3. 17 3. 12 3. 07 3. 03 2. 99 2. 84 2. 66 2. 50 2. 34 2. 18 15 6157 99. 4 26. 9 14. 2 9. 72 7. 56 6. 31 5. 52 4. 96 4. 56 4. 25 4. 01 3. 82 3. 66 3. 52 3. 41 3. 31 3. 23 3. 15 3. 09 3. 03 2. 98 2. 93 2. 89 2. 85 2. 70 2. 52 2. 35 2. 19 2. 04 20 6209 99. 4 26. 14. 0 9. 55 7. 40 6. 16 5. 36 4. 81 4. 41 4. 10 3. 86 3. 66 3. 51 3. 37 3. 26 3. 16 3. 08 3. 00 2. 94 2. 88 2. 83 2. 78 2. 74 2. 70 2. 55 2. 37 2. 20 2. 03 1. 88 24 6235 99. 5 26. 6 13. 9 9. 47 7. 31 6. 07 5. 28 4. 73 4. 33 4. 02 3. 78 3. 59 3. 43 3. 29 3. 18 3. 08 3. 00 2. 92 2. 86 2. 80 2. 75 2. 70 2. 66 2. 62 2. 47 2. 29 2. 12 1. 95 1. 79 30 6261 99. 5 26. 5 13. 8 9. 38 7. 23 5. 99 5. 20 4. 65 4. 25 3. 94 3. 70 3. 51 3. 35 3. 21 3. 10 3. 00 2. 92 2. 84 2. 78 2. 72 2. 67 2. 62 2. 58 2. 54 2. 39 2. 20 2. 03 1. 86 1. 70 40 6287 99. 5 26. 4 13. 7 9. 29 7. 14 5. 91 5. 12 4. 57 4. 17 3. 86 3. 62 3. 43 3. 27 3. 13 3. 02 2. 92 2. 84 2. 6 2. 69 2. 64 2. 58 2. 54 2. 49 2. 45 2. 30 2. 11 1. 94 1. 76 1. 59 Degrees of Freedom for the Denominator 274 Appendixes Appendix H Critical Values of Chi-Square This table contains the values of of degrees of freedom. 2 that correspond to a specific right-tail area and specific number Example: With 17 df and a . 02 area in the upper tail, 2 30. 995 0 Degrees of Freedom, df 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 2 Right-Tail Area 0. 10 2. 706 4. 605 6. 251 7. 779 9. 236 10. 645 12. 017 13. 362 14. 684 15. 987 17. 275 18. 549 19. 812 21. 064 22. 307 23. 542 24. 769 25. 989 27. 204 28. 12 29. 615 30. 813 32. 007 33. 196 34. 382 35. 563 36. 741 37. 916 39. 087 40. 256 0. 05 3. 841 5. 991 7. 815 9. 488 11. 070 12. 592 14. 067 15. 507 16. 919 18. 307 19. 675 21. 026 22. 362 23. 685 24. 996 26. 296 27. 587 28. 869 30. 144 31. 410 32. 671 33. 924 35. 172 36. 415 37. 652 38. 885 40. 113 41. 337 42. 557 43. 773 0. 02 5. 412 7. 824 9. 837 11. 668 13. 388 15. 033 16. 622 18. 168 19. 679 21. 161 22. 618 24. 054 25. 472 26. 873 28. 259 29. 633 30. 995 32. 346 33. 687 35. 020 36. 343 37. 659 38. 968 40. 270 41. 566 42. 856 44. 140 45. 419 46. 693 47. 962 0. 01 6. 635 9. 210 11. 345 13. 277 15. 086 16. 812 18. 475 20. 090 21. 66 23. 209 24. 725 26. 217 27. 688 29. 141 30. 578 32. 000 33. 409 34. 805 36. 191 37. 566 38. 932 40. 289 41. 638 42. 980 44. 314 45. 642 46. 963 48. 278 49. 588 50. 892 Tables and Data Sets 275 Appendix I Binomial Probability Distribution n x 0 1 0. 05 0. 950 0. 050 0. 10 0. 900 0. 100 0. 20 0. 800 0. 200 0. 30 0. 700 0. 300 0. 40 0. 600 0. 400 1 0. 50 0. 500 0. 500 0. 60 0. 400 0. 600 0. 70 0. 300 0. 700 0. 80 0. 200 0. 800 0. 90 0. 100 0. 900 0. 95 0. 050 0. 950 Probability n 2 Probability x 0 1 2 0. 05 0. 903 0. 095 0. 003 0. 10 0. 810 0. 180 0. 010 0. 20 0. 640 0. 320 0. 040 0. 30 0. 490 0. 420 0. 090 0. 40 0. 360 0. 480 0. 60 0. 50 0. 250 0. 500 0. 250 0. 60 0. 160 0. 480 0. 360 0. 70 0. 090 0. 420 0. 490 0. 80 0. 040 0. 320 0. 640 0. 90 0. 010 0. 180 0. 810 0. 95 0. 003 0. 095 0. 903 n 3 Probability x 0 1 2 3 0. 05 0. 857 0. 135 0. 007 0. 000 0. 10 0. 729 0. 243 0. 027 0. 001 0. 20 0. 512 0. 384 0. 096 0. 008 0. 30 0. 343 0. 441 0. 189 0. 027 0. 40 0. 216 0. 432 0. 288 0. 064 0. 50 0. 125 0. 375 0. 375 0. 125 0. 60 0. 064 0. 288 0. 432 0. 216 0. 70 0. 027 0. 189 0. 441 0. 343 0. 80 0. 008 0. 096 0. 384 0. 512 0. 90 0. 001 0. 027 0. 243 0. 729 0. 95 0. 000 0. 007 0. 135 0. 857 n 4 Probability x 0 1 2 3 4 0. 05 0. 815 0. 171 0. 014 0. 000 0. 000 0. 0 0. 656 0. 292 0. 049 0. 004 0. 000 0. 20 0. 410 0. 410 0. 154 0. 026 0. 002 0. 30 0. 240 0. 412 0. 265 0. 076 0. 008 0. 40 0. 130 0. 346 0. 346 0. 154 0. 026 0. 50 0. 063 0. 250 0. 375 0. 250 0. 063 0. 60 0. 026 0. 154 0. 346 0. 346 0. 130 0. 70 0. 008 0. 076 0. 265 0. 412 0. 240 0. 80 0. 002 0. 026 0. 154 0. 410 0. 410 0. 90 0. 000 0. 004 0. 049 0. 292 0. 656 0. 95 0. 000 0. 000 0. 014 0. 171 0. 815 n 5 Probability x 0 1 2 3 4 5 0. 05 0. 774 0. 204 0. 021 0. 001 0. 000 0. 000 0. 10 0. 590 0. 328 0. 073 0. 008 0. 000 0. 000 0. 20 0. 328 0. 410 0. 205 0. 051 0. 006 0. 000 0. 30 0. 168 0. 360 0. 309 0. 132 0. 028 0. 002 0. 40 0. 78 0. 259 0. 346 0. 230 0. 077 0. 010 0. 50 0. 031 0. 156 0. 313 0. 313 0. 156 0. 031 0. 60 0. 010 0. 077 0. 230 0. 346 0. 259 0. 078 0. 70 0. 002 0. 028 0. 132 0. 309 0. 360 0. 168 0. 80 0. 000 0. 006 0. 051 0. 205 0. 410 0. 328 0. 90 0. 000 0. 000 0. 008 0. 073 0. 328 0. 590 0. 95 0. 000 0. 000 0. 001 0. 021 0. 204 0. 774 n 6 Probabili ty x 0 1 2 3 4 5 6 0. 05 0. 735 0. 232 0. 031 0. 002 0. 000 0. 000 0. 000 0. 10 0. 531 0. 354 0. 098 0. 015 0. 001 0. 000 0. 000 0. 20 0. 262 0. 393 0. 246 0. 082 0. 015 0. 002 0. 000 0. 30 0. 118 0. 303 0. 324 0. 185 0. 060 0. 010 0. 001 0. 40 0. 047 0. 187 0. 311 0. 276 0. 138 0. 037 0. 004 0. 0 0. 016 0. 094 0. 234 0. 313 0. 234 0. 094 0. 016 0. 60 0. 004 0. 037 0. 138 0. 276 0. 311 0. 187 0. 047 0. 70 0. 001 0. 010 0. 060 0. 185 0. 324 0. 303 0. 118 0. 80 0. 000 0. 002 0. 015 0. 082 0. 246 0. 393 0. 262 0. 90 0. 000 0. 000 0. 001 0. 015 0. 098 0. 354 0. 531 0. 95 0. 000 0. 000 0. 000 0. 002 0. 031 0. 232 0. 735 276 Appendixes Appendix I Binomial Probability Distribution (continued) n 7 Probability x 0 1 2 3 4 5 6 7 0. 05 0. 698 0. 257 0. 041 0. 004 0. 000 0. 000 0. 000 0. 000 0. 10 0. 478 0. 372 0. 124 0. 023 0. 003 0. 000 0. 000 0. 000 0. 20 0. 210 0. 367 0. 275 0. 115 0. 029 0. 004 0. 000 0. 000 0. 30 0. 082 0. 247 0. 18 0. 227 0. 097 0. 025 0. 004 0. 000 0. 40 0. 028 0. 131 0 . 261 0. 290 0. 194 0. 077 0. 017 0. 002 0. 50 0. 008 0. 055 0. 164 0. 273 0. 273 0. 164 0. 055 0. 008 0. 60 0. 002 0. 017 0. 077 0. 194 0. 290 0. 261 0. 131 0. 028 0. 70 0. 000 0. 004 0. 025 0. 097 0. 227 0. 318 0. 247 0. 082 0. 80 0. 000 0. 000 0. 004 0. 029 0. 115 0. 275 0. 367 0. 210 0. 90 0. 000 0. 000 0. 000 0. 003 0. 023 0. 124 0. 372 0. 478 0. 95 0. 000 0. 000 0. 000 0. 000 0. 004 0. 041 0. 257 0. 698 n 8 Probability x 0 1 2 3 4 5 6 7 8 0. 05 0. 663 0. 279 0. 051 0. 005 0. 000 0. 000 0. 000 0. 000 0. 000 0. 10 0. 430 0. 383 0. 149 0. 033 0. 005 0. 000 0. 000 0. 000 0. 00 0. 20 0. 168 0. 336 0. 294 0. 147 0. 046 0. 009 0. 001 0. 000 0. 000 0. 30 0. 058 0. 198 0. 296 0. 254 0. 136 0. 047 0. 010 0. 001 0. 000 0. 40 0. 017 0. 090 0. 209 0. 279 0. 232 0. 124 0. 041 0. 008 0. 001 0. 50 0. 004 0. 031 0. 109 0. 219 0. 273 0. 219 0. 109 0. 031 0. 004 0. 60 0. 001 0. 008 0. 041 0. 124 0. 232 0. 279 0. 209 0. 090 0. 017 0. 70 0. 000 0. 001 0. 010 0. 047 0. 136 0. 254 0. 296 0. 198 0. 0 58 0. 80 0. 000 0. 000 0. 001 0. 009 0. 046 0. 147 0. 294 0. 336 0. 168 0. 90 0. 000 0. 000 0. 000 0. 000 0. 005 0. 033 0. 149 0. 383 0. 430 0. 95 0. 000 0. 000 0. 000 0. 000 0. 000 0. 005 0. 051 0. 279 0. 663 n 9 Probability x 1 2 3 4 5 6 7 8 9 0. 05 0. 630 0. 299 0. 063 0. 008 0. 001 0. 000 0. 000 0. 000 0. 000 0. 000 0. 10 0. 387 0. 387 0. 172 0. 045 0. 007 0. 001 0. 000 0. 000 0. 000 0. 000 0. 20 0. 134 0. 302 0. 302 0. 176 0. 066 0. 017 0. 003 0. 000 0. 000 0. 000 0. 30 0. 040 0. 156 0. 267 0. 267 0. 172 0. 074 0. 021 0. 004 0. 000 0. 000 0. 40 0. 010 0. 060 0. 161 0. 251 0. 251 0. 167 0. 074 0. 021 0. 004 0. 000 0. 50 0. 002 0. 018 0. 070 0. 164 0. 246 0. 246 0. 164 0. 070 0. 018 0. 002 0. 60 0. 000 0. 004 0. 021 0. 074 0. 167 0. 251 0. 251 0. 161 0. 060 0. 010 0. 70 0. 000 0. 000 0. 004 0. 021 0. 074 0. 172 0. 267 0. 267 0. 156 0. 040 0. 80 0. 00 0. 000 0. 000 0. 003 0. 017 0. 066 0. 176 0. 302 0. 302 0. 134 0. 90 0. 000 0. 000 0. 000 0. 000 0. 001 0. 007 0. 045 0. 172 0. 387 0. 387 0. 95 0. 000 0. 000 0. 000 0. 000 0. 000 0. 001 0. 008 0. 063 0. 299 0. 630 n 10 Probability x 0 1 2 3 4 5 6 7 8 9 10 0. 05 0. 599 0. 315 0. 075 0. 010 0. 001 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 10 0. 349 0. 387 0. 194 0. 057 0. 011 0. 001 0. 000 0. 000 0. 000 0. 000 0. 000 0. 20 0. 107 0. 268 0. 302 0. 201 0. 088 0. 026 0. 006 0. 001 0. 000 0. 000 0. 000 0. 30 0. 028 0. 121 0. 233 0. 267 0. 200 0. 103 0. 037 0. 00 0. 001 0. 000 0. 000 0. 40 0. 006 0. 040 0. 121 0. 215 0. 251 0. 01 0. 111 0. 042 0. 011 0. 002 0. 000 0. 50 0. 001 0. 010 0. 044 0. 117 0. 205 0. 246 0. 205 0. 117 0. 044 0. 010 0. 001 0. 60 0. 000 0. 002 0. 011 0. 042 0. 111 0. 201 0. 251 0. 215 0. 121 0. 040 0. 006 0. 70 0. 000 0. 000 0. 001 0. 009 0. 037 0. 103 0. 200 0. 267 0. 233 0. 121 0. 028 0. 80 0. 000 0. 000 0. 000 0. 001 0. 006 0. 026 0. 088 0. 201 0. 302 0. 268 0. 107 0. 90 0. 000 0. 000 0. 000 0. 000 0. 000 0. 001 0. 011 0. 057 0. 194 0. 387 0. 349 0. 95 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 001 0. 010 0. 075 0. 315 0. 599 Tables and Data Sets 277 Appendix I Binomial Probability Distribution (continued) n 11 Probability x 1 2 3 4 5 6 7 8 9 10 11 0. 05 0. 569 0. 329 0. 087 0. 014 0. 001 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 10 0. 314 0. 384 0. 213 0. 071 0. 016 0. 002 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 20 0. 086 0. 236 0. 295 0. 221 0. 111 0. 039 0. 010 0. 002 0. 000 0. 000 0. 000 0. 000 0. 30 0. 020 0. 093 0. 200 0. 257 0. 220 0. 132 0. 057 0. 017 0. 004 0. 001 0. 000 0. 000 0. 40 0. 004 0. 027 0. 089 0. 177 0. 236 0. 221 0. 147 0. 070 0. 023 0. 005 0. 001 0. 000 0. 50 0. 000 0. 005 0. 027 0. 081 0. 161 0. 226 0. 226 0. 161 0. 081 0. 027 0. 005 0. 000 0. 60 0. 000 0. 001 0. 005 0. 023 0. 070 0. 147 0. 221 0. 236 0. 177 0. 89 0. 027 0. 004 0. 70 0. 000 0. 000 0. 001 0. 004 0. 017 0. 057 0. 132 0. 220 0. 257 0. 200 0. 093 0. 020 0. 80 0. 000 0. 000 0. 000 0. 000 0. 002 0. 010 0. 039 0. 111 0. 221 0. 295 0. 236 0. 086 0. 90 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 002 0. 016 0. 071 0. 213 0. 384 0. 314 0. 95 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 001 0. 014 0. 087 0. 329 0. 569 n 12 Probability x 0 1 2 3 4 5 6 7 8 9 10 11 12 0. 05 0. 540 0. 341 0. 099 0. 017 0. 002 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 10 0. 282 0. 377 0. 230 0. 085 0. 021 0. 004 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 20 0. 069 0. 206 0. 83 0. 236 0. 13 3 0. 053 0. 016 0. 003 0. 001 0. 000 0. 000 0. 000 0. 000 0. 30 0. 014 0. 071 0. 168 0. 240 0. 231 0. 158 0. 079 0. 029 0. 008 0. 001 0. 000 0. 000 0. 000 0. 40 0. 002 0. 017 0. 064 0. 142 0. 213 0. 227 0. 177 0. 101 0. 042 0. 012 0. 002 0. 000 0. 000 0. 50 0. 000 0. 003 0. 016 0. 054 0. 121 0. 193 0. 226 0. 193 0. 121 0. 054 0. 016 0. 003 0. 000 0. 60 0. 000 0. 000 0. 002 0. 012 0. 042 0. 101 0. 177 0. 227 0. 213 0. 142 0. 064 0. 017 0. 002 0. 70 0. 000 0. 000 0. 000 0. 001 0. 008 0. 029 0. 079 0. 158 0. 231 0. 240 0. 168 0. 071 0. 014 0. 80 0. 000 0. 000 0. 000 0. 000 0. 001 0. 003 0. 016 0. 053 0. 133 0. 236 0. 83 0. 206 0. 069 0. 90 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 004 0. 021 0. 085 0. 230 0. 377 0. 282 0. 95 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 002 0. 017 0. 099 0. 341 0. 540 n 13 Probability x 0 1 2 3 4 5 6 7 8 9 10 11 12 13 0. 05 0. 513 0. 351 0. 111 0. 021 0. 003 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 10 0. 254 0. 367 0. 245 0. 100 0. 028 0. 006 0. 001 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 20 0. 055 0. 179 0. 268 0. 246 0. 154 0. 069 0. 023 0. 006 0. 001 0. 000 0. 000 0. 000 0. 000 0. 000 0. 30 0. 010 0. 054 0. 139 0. 218 0. 234 0. 180 0. 103 0. 044 0. 14 0. 003 0. 001 0. 000 0. 000 0. 000 0. 40 0. 001 0. 011 0. 045 0. 111 0. 184 0. 221 0. 197 0. 131 0. 066 0. 024 0. 006 0. 001 0. 000 0. 000 0. 50 0. 000 0. 002 0. 010 0. 035 0. 087 0. 157 0. 209 0. 209 0. 157 0. 087 0. 035 0. 010 0. 002 0. 000 0. 60 0. 000 0. 000 0. 001 0. 006 0. 024 0. 066 0. 131 0. 197 0. 221 0. 184 0. 111 0. 045 0. 011 0. 001 0. 70 0. 000 0. 000 0. 000 0. 001 0. 003 0. 014 0. 044 0. 103 0. 180 0. 234 0. 218 0. 139 0. 054 0. 010 0. 80 0. 000 0. 000 0. 000 0. 000 0. 000 0. 001 0. 006 0. 023 0. 069 0. 154 0. 246 0. 268 0. 179 0. 055 0. 90 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 001 0. 006 0. 028 0. 00 0. 245 0. 367 0. 254 0. 95 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 003 0. 021 0. 111 0. 351 0. 513 278 Appendixes Appendix I Binomial Probability Distribution (continued) n 14 Probability x 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 0. 05 0. 488 0. 359 0. 123 0. 026 0. 004 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 10 0. 229 0. 356 0. 257 0. 114 0. 035 0. 008 0. 001 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 20 0. 044 0. 154 0. 250 0. 250 0. 172 0. 086 0. 032 0. 009 0. 002 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 30 0. 007 0. 041 0. 113 0. 194 0. 229 0. 196 0. 26 0. 062 0. 023 0. 007 0. 001 0. 000 0. 000 0. 000 0. 000 0. 40 0. 001 0. 007 0. 032 0. 085 0. 155 0. 207 0. 207 0. 157 0. 092 0. 041 0. 014 0. 003 0. 001 0. 000 0. 000 0. 50 0. 000 0. 001 0. 006 0. 022 0. 061 0. 122 0. 183 0. 209 0. 183 0. 122 0. 061 0. 022 0. 006 0. 001 0. 000 0. 60 0. 000 0. 000 0. 001 0. 003 0. 014 0. 041 0. 092 0. 157 0. 207 0. 207 0. 155 0. 085 0. 032 0. 007 0. 001 0. 70 0. 000 0. 000 0. 000 0. 000 0. 001 0. 007 0. 023 0. 062 0 . 126 0. 196 0. 229 0. 194 0. 113 0. 041 0. 007 0. 80 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 002 0. 009 0. 032 0. 086 0. 172 0. 250 0. 250 0. 154 0. 044 0. 90 0. 000 0. 000 0. 00 0. 000 0. 000 0. 000 0. 000 0. 000 0. 001 0. 008 0. 035 0. 114 0. 257 0. 356 0. 229 0. 95 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 004 0. 026 0. 123 0. 359 0. 488 n 15 Probability x 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 0. 05 0. 463 0. 366 0. 135 0. 031 0. 005 0. 001 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 10 0. 206 0. 343 0. 267 0. 129 0. 043 0. 010 0. 002 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 20 0. 035 0. 132 0. 231 0. 250 0. 188 0. 103 0. 043 0. 014 0. 003 0. 001 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 30 0. 005 0. 031 0. 092 0. 70 0. 219 0. 206 0. 147 0. 081 0. 035 0. 012 0. 003 0. 001 0. 000 0. 000 0. 000 0. 000 0. 40 0. 000 0. 005 0. 022 0. 063 0. 127 0. 186 0. 207 0. 177 0. 118 0. 061 0. 024 0. 007 0. 002 0. 000 0. 000 0. 000 0. 50 0. 000 0. 000 0. 003 0. 014 0. 042 0. 092 0. 153 0. 196 0. 196 0. 153 0. 092 0. 042 0. 014 0. 003 0. 000 0. 000 0. 60 0. 000 0. 000 0. 000 0. 002 0. 007 0. 024 0. 061 0. 118 0. 177 0. 207 0. 186 0. 127 0. 063 0. 022 0. 005 0. 000 0. 70 0. 000 0. 000 0. 000 0. 000 0. 001 0. 003 0. 012 0. 035 0. 081 0. 147 0. 206 0. 219 0. 170 0. 092 0. 031 0. 005 0. 80 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 001 0. 003 0. 014 0. 043 0. 03 0. 188 0. 250 0. 231 0. 132 0. 035 0. 90 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 002 0. 010 0. 043 0. 129 0. 267 0. 343 0. 206 0. 95 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 001 0. 005 0. 031 0. 135 0. 366 0. 463 n 16 Probability x 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 0. 05 0. 440 0. 371 0. 146 0. 036 0. 006 0. 001 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 10 0. 185 0. 329 0. 275 0. 142 0. 051 0. 014 0. 003 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 20 0. 028 0. 113 0. 211 0. 246 0. 200 0. 120 0. 055 0. 20 0. 006 0. 001 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 30 0. 003 0. 023 0. 073 0. 146 0. 204 0. 210 0. 165 0. 101 0. 049 0. 019 0. 006 0. 001 0. 000 0. 000 0. 000 0. 000 0. 000 0. 40 0. 000 0. 003 0. 015 0. 047 0. 101 0. 162 0. 198 0. 189 0. 142 0. 084 0. 039 0. 014 0. 004 0. 001 0. 000 0. 000 0. 000 0. 50 0. 000 0. 000 0. 002 0. 009 0. 028 0. 067 0. 122 0. 175 0. 196 0. 175 0. 122 0. 067 0. 028 0. 009 0. 002 0. 000 0. 000 0. 60 0. 000 0. 000 0. 000 0. 001