2 response Essay Example | Topics and Well Written Essays - 500 words

2 response - Essay Example The essay also conveys the beautiful message that one should love oneself in the very natural manner that one is born with and should not listen or act according to what others have to say about them. It also emphasizes on the fact that it is the values that are found within a girl that makes her more beautiful rather than the cosmetic covered face. There is no point in hurting oneself at the behest of others who are always ready to point out only the bad parts of something and not the good ones. 2. The author needs to come up with either any textual help from an essay or a personal story to prove her allegations regarding the singer Shakira. It was just her opinion that she has given in the essay about the singer and there is no valid proof to prove the fact that she has incorporated in her work about the singer. Wearing provocative clothing and moving her hips are just personal comments that the author has given to the singer. The author should have provided certain proved facts or the views of some other writers to discuss her views. By providing her view points only, the author has given rise to a weak point in the essay which may be criticized by others who read it. 3. The weakest part that the essay contains is that it bases its deductions and relies its studies on flimsy poetry and imaginative ideas. It compares the very practical aspects in reality to the imaginative concepts of poetries and stories. Moreover it takes into account the very tiny age of girls which is not the correct thing to be done. The magazines and the books that the author talks about are for women. The age group of children that the author talks about is not this rather that of small girls who are not at all connected with the magazine part. Thus there is no coherence in the writing. There could have been stronger points in the essay if it would have the proper coherence required and if it could provide the readers with more clarity about the

Essay --

Globalization: Jobs: How Foreign Laborers Can Affect the U.S. Economy The economy is becoming increasingly global. Business face complex decisions when conducting operations, as business boundaries are no longer stated in national terms, but instead in global terms. For instance, management for companies ranging from medical information technology to software engineering must ask questions, such as: From what company should our company purchase input parts for our latest medical diagnostic equipment? Or should we outsource our manufacturing process for laptop computers overseas? Or how will globalization affect return to our investors for our latest software development subsidiary? Outsourcing is among one of the economic decisions businesses of all sizes must face. U.S. Corporations have high incentive to outsource job functions to foreign markets, as the wages of a foreign worker are a fraction of the domestic counterpart. The incentive is especially high to outsource to emerging markets such as China and India. According to a study conducted by the U.S. Bureau of Labor Statistics in 2010, a production worker in India would work for an average of 92 cents an hour as compared to a U.S. worker who would not be able to legally obtain employment for any less than the U.S. minimum wage of $7.25 an hour (U.S. BLS, 2010). At that time, India labor cost just 13% of U.S. labor. Imagine a U.S. corporation competing with businesses that incur labor costs that are only 13% of the U.S. equivalent; in order for that business to remain profitable, they would outsource as many functions as possible. Outsourcing trends are unlikely to change, at least in the short-term futu re. Historically, outsourcing has occurred in labor intensive indust... ...oduct, is a formula that economists use to measure economic growth. GDP in China has grown at an average ___, whereas U.S. GDP has grown at ___ for the same period of ___. A reason behind this phenomenon is that developing countries typically grow at a faster economic pace than more industrialized nations. When the United States economy was industrializing, GDP grew at a pace of†¦. Modern economic theory demonstrates that some developing nations will eventually approach the economic wealth of more developed nations. In may not happen for at least fifty years, but eventually wage differences will substantially lessen, at least in terms of national boundaries. Foreign labor cost is currently a factor that aids firms in achieving an advantage in the market place. In the far future it is unlikely that the price of labor will be much different across national boundaries.

Why Do People Use Drugs?

PSY215: DRUGS AND DEPENDENCY ESSAY ONE WHY DO PEOPLE USE DRUGS? LACHLAN SLOAN 30790798 Throughout history, people have used different kinds of drugs to alter the way they feel or experience consciousness. Ritualistic use of drugs has been commonly practiced by various cultures such as the mushroom induced trance state utilised by Native American Indians to commune with the Great Spirit. Pacific Islanders drink Kava as a means of connecting with the supernatural, healing illness and welcoming guests to the community.Whilst Indians referred to being consciously high as the state of ‘Shiva’ and associated this process with the worship of one of their prime deities, Shiva. Over time the ritualistic use of drugs has integrated as a part of modern society which can be observed in celebrations such as weddings and birthdays where alcohol is commonly consumed. As there is such a vast range of drugs and influences available with many established uses and categorisations the proce ss of determining why people use drugs becomes intricate very rapidly.Norman E Zinberg developed a theory on drug use which is a widely accepted public health model. The basis of this theory argues that it is not possible to understand drug use, the effects or the outcomes of the drug experience unless you take into account the interrelationship of factors between: the drug, the environment and the individual (Zinberg, 1986). For the purpose of this analysis various aspects of influence have been categorised based on Zinberg’s theory to coherently convey why people use drugs.The categorizations are as follows: Individual (cognition, genetics, and physical/psychological state), drug (perceived functions of drug use in society/specific purpose for using a particular substance, drug related expectancies and compulsive use) and environment (social/contextual level). Boys et al (2001) recorded among a study of 364 participants that had used cannabis over the past year that, the tw o most popular reasons for using the drug were to ‘just get really stoned or intoxicated’ (90. 7%) and ‘help you to relax’ (96. 8%). People using drugs often state that they use them to feel ‘good’.What makes these people feel ‘good’ is the way in which the chemicals in these drugs influence cognition. This state of feeling ‘good’ and or being high is attained because most drugs act on the limbic system in the brain, referred to as the ‘pleasure centre’. The presynaptic terminal releases the neurotransmitters Dopamine, Noradrenaline and Serotonin via nerves located at the terminal. These neurotransmitters are released and travel to the post synaptic terminal where specific receptor sites are located on the nerve cell for each neurotransmitter.Here nerve action potential is developed via neurotransmitter action on the receptor site. Prevalent drugs act by blocking, mimicking or stimulating the release of ne urotransmitters via the presynaptic terminal. When Dopamine levels are increased, mimicked or reuptake is permitted (blocked) the reward pathway in the brain is affected which when stimulated creates feelings of pleasure and euphoria (pleasure is associated with reward). The ingested drug is hence associated with pleasure and reward and the person is influenced to continue using the particular drug.Current cognitive-motivational theories of addiction assert that prioritising appetitive, reward-related information plays an inherent role in the development and continuation of substance abuse (Field & Cox, 2008; Franken, 2003; Wiers et al 2007). A study focused on reward-related attentional processes among 682 young adolescents (mean age= 16. 14) had participants complete a motivated game in the format of a spatial orienting task as a behavioural index of appetitive-related attentional processes and a questionnaire to index substance (alcohol, tobacco, and cannabis) use.Correlational a nalysis showed a positive relationship between substance use and enhanced attentional engagement, with cues that predicted potential reward and non- punishment (Ostafin et al, 2013). Research since the mid 1960’s has established that genetics play a modest (yet relevant) role in the development of drug use problems in some individuals (Pickens, 1988; Farrell & Strang, 1992; Hill, 1993). It has been conveyed by Mcgue (1994) that genetics have an influence on a person’s disposition to use drugs.After a review of literature on genetics research in relation to alcoholism, Mcgue established that genetic factors exert a moderate influence on male and female risk for alcoholism. It has been suggested by Hansler (2001) that mental illness motivates sufferers to take drugs (prescription and recreational), this process can cause drug problems (when a person takes drugs in the hope of escaping their symptoms or becomes dependent on a prescription drug). Examples include a person suffering from social anxiety ingesting cocaine in order to temperamentally enhance their sociability when going out with friends.Most of the evidence, however, seems to indicate that these factors can lead to problems; that is, biological, social and/or environmental factors predispose a person to have both a mental health and a substance abuse problem. Aesthetics and physicality are also motivators for drug use. A person will ingest substances to alter the physical nature of their body, primarily due to the fact that they are not satisfied with a particular aspect of their physical self. Examples include; performance enhancing drugs (steroids), Viagra and antibiotics.In beginning the process of analysing the perceived functions of drug use/specific purpose for using a particular substance, psychoactive drugs are the first place to start as due to the broad range of this category. The classification of psychoactive drugs is sub divided into three categories (with some drugs falling into more than one category); Depressants, Stimulants and Hallucinogens. Depressants work by inhibiting the activity of the CNS (Central Nervous System), which slows down various bodily functions such as heart rate and breathing.This classification of drugs has with it a reputation inherent within society as having a calming effect (popularised primarily due to alcohol its acceptance and availability). People generally take this type of drug to relax, another primary function and motivation of the use of depressants is to combat the effects of stress and anxiety (reduces nerves and relaxes muscle). These drugs are typically easy to obtain being available illegally and legally. Examples include acquiring a depressant legally via a doctor’s prescription or benzodiazepines to treat anxiety and purchasing marijuana from a local drug dealer in order to alleviate stress from work. Stimulants work by stimulating the CNS (increasing brain activity) which causes the body to become mo re aroused and responsive. Hence stimulants elevate the mood, create excitement and even induce a state of euphoria. Due to the nature of stimulants improving responsiveness this category of drug is associated with increasing people’s energy levels as brain activity is dramatically increased.Stimulants are widely available legally and illegally with the most common being caffeine, which is the most widely used drug in the world (Julien, 2001). Hallucinogens are a class of drug that alter perceptual functions; sight, hearing, smell, taste or physical touch. Hallucinogens disrupt how the nerve cells and the neurotransmitter serotonin interact with the CNS. By altering the natural levels of serotonin in the body, hallucinogens alter the way in which your brain processes information relevant to perceptual functions.The inhibition of the user’s perceptual functions allows for the body to generate an intense high. Hence many users of hallucinogens utilise this type of drug t o experience the intensity of the high and/or to escape reality. Examples of hallucinogens include; magic mushrooms, marijuana and LSD. A web based survey of 96 (50 female, 46 male) regular drinking college students over a ten week period) reported on their previous week alcohol use and experience of 24 alcohol-related consequences, including their subjective evaluations of those consequences.Most notably of the results, hierarchical linear model tests revealed that students drank less and experienced fewer consequences following weeks in which they rated their consequences as more negative (relative to their own typical subjective evaluations), suggesting that viewing one’s recent consequences as aversive prompts self-initiated behaviour change. It was conveyed by Boys et al (1999) that significant relationships between perceived functions and both the persons intentions to use the drug again in the future and the recent use of a particular drug.Data was collected from a cro ss sectional survey of one hundred participants aged 16 – 21 years of age. Higher scores on a five item social/contextual function scale (Eg. using a drug to help you feel more confident in a social situation) were associated with a greater frequency of recent cannabis use. Drug expectancy is a psychoactive process that occurs as a response to an individual’s expectation that a drug induced effect will occur. Drug expectancy divulges the nature of a person desire to experience the effects from a particular drug(s).The effect occurs from a person’s own experience with a drug, education, feedback from peers/family and media influence. Once acquired via direct experience with a drug, the memory network of positive expectancies can be primed by internal or external drug associated cues. Primed expectancies are thought to guide subsequent drug use (Hersen, 2013). Self-reports from 704 college students were content analysed and used to develop the Marijuana Effect Exp ectancy Questionnaire. Responses were examined using exploratory and confirmatory principle components analysis.Six marijuana expectancies (34. 6% of variance) were identified: (a) cognitive and behavioural impairment, (b) relaxation and tension reduction, (c) social and sexual facilitation, (d) perceptual and cognitive enhancement, (e) global negative effects, and (f) craving and physical effects (Schafer & Brown, 1991). When a person begins using a drug on a regular basis they begin to become dependent on the drug. As tolerance towards the drug grows in the person they become more dependent on the drug in order to achieve the same effect they attained from their first usage.Drug dependency can manifest in both physical/psychological forms. This can be classified in the sense that the body requires the drug to function properly relating to either form of classification. When a person abstains from retaining the normal level of the abused drug in their blood withdrawal symptoms begi n to act. Those with a physiological dependency experience physical discomfort, shaking, nausea and vomiting as withdrawal symptoms. People with a Psychological dependence feel depressive, anxious, aggressive and irritated.Research supports the belief that the negative nature of withdrawal symptoms is associated with drug users continued abuse of a certain drug (Rogers, 2002). Social/contextual level influences have a massive level of governance over a person’s rationalising to use drugs. College students say they utilise alcohol and drugs in order to lessen depression, increase sociability, satisfy curiosity, heighten sexual pleasure, alleviate physical discomfort and expand consciousness (Robbins et al. , 1970). Association with peers tilising drugs is one of the strongest predictors of adolescent drug use (Fergusson et al, 1995; Brook et al, 1990). If other members of the group begin using drugs, some people are influenced to trade sobriety for use in order to fit in and a dapt to the group. Motivation for this exists in the individual wanting to conform to the dynamics of the group paired with fear of rejection from the group. An example of this is conveyed by Hohman et al (2013) via a study of data obtained from the National Survey of Parents and Youth (N= 1,604).Two hierarchical multiple regression models were developed examining the association between ambivalent attitudes, intentions and later marijuana use. The hierarchical models consisted of; an analysis of the moderating effect of ambivalence on the persons intent to use marijuana and the testing of the moderation of ambivalence on literal marijuana use a year later. Results from both hierarchical analyses propose that ambivalence moderated the association of friend norms and subsequent adolescent marijuana use: friend norms were better predictors of marijuana intentions (? 0. 151, t = 2. 29, p = 0. 02) and subsequent use when adolescents were attitudinally ambivalent about marijuana use (? = 0. 071, t = 2. 76, p = 0. 006). The environment of a person greatly influences their susceptibility to drug use. Not only does the social context of a person influence drug use but the environment itself plays a very influential role. A study undertaken in Zinberg’s ‘Drug, Set, And Setting: The Basis For Controlled Intoxicant Use’, analysed a group of American soldiers who began using and became addicted to heroin during the Vietnam war.After the war effort, usage â€Å"virtually ceased†, with only 12% of the soldiers remaining addicted after returning back to the United States. It is evident that these American soldiers were utilising heroin as a form of escapism, a way to disassociate themselves from the harsh reality they were situated in. Hence it can be expected that a person’s socioeconomic status would affect their use of drugs. People living in a negative environment and/or of a lower socio economic status would be more likely to turn to dr ug use as a means of dealing with and escaping their predicament.In the process of determining why people use drugs a diverse range of conclusions have been reached via a model representative of Zinberg’s theory. We began by stating the ritual usages practiced for thousands of years which have transcended into society after society. We begin with Zinberg’s notion of the individual and diverge into the way in which human cognition is affected by drugs. As this topic is explored it is conveyed just how susceptible our brains are to drug use and why we enjoy the temperamental effects drugs create.Genetics, physical and psychological disposition are also conveyed as influencing reasoning for drug use. Drugs are addressed via the perceived functions of illegal and legal drugs by an analysis of drug categorisations where perceived functions and reasons for use are conveyed. Drug expectancy and tolerance is explained and the reasoning for continued use and addiction is commun icated via a study by Schafer & Brown (1991). The social/contextual level of influence is analysed via various studies by Zinberg (1986) and Hohman (2013) conveying environmental and social influences.People ingest a diversity of different drugs for a variety of different reasons; socialisation, environmental factors, perceived norms, to relax, pleasure, to conform, genetics, addiction, out of boredom or curiosity or to escape their problems. Reference List Boys, A. , Marsden, J. , Fountain, J. , Griffiths, P. , Stillwell, G. , & Strang, J. (1999). What influences young people's use of drugs? A qualitative study of decision-making. Drugs: Education, Prevention and Policy,  6,  373–389. Boys, A. , Marsden, J. , ; Strang, J. 2001) Understanding reasons for drug use amongst young people: a functional perspective. Health Education Research, 16  (4), 457-469. DOI:  10. 1093/her/16. 4. 457. Field, M. , ; Cox, W. M. (2008). Attentional bias in addictive behaviours: a review of its development, causes, and consequences. American Journal of Psychology, 84, 349 – 358 DOI: 10. 1016/j. drugalcdep. 2008. 03. 030. Franken, I. H. (2003). Drug craving and addiction: integrating psychological and neuropsychopharmacological approaches, 4, 563 – 79. Hansler, V. (2001).The Inherent Disposition to Drug Abuse, 9, 32 – 47, New York: Worth Publishers. Hersen, M. (2013). Principles of Addiction: Comprehensive Addictive Behaviours and Disorders, 1, 426 – 429 Hill, W. G. (1993). Variation in genetic composition in back crossing programs, 84, 212-213. Hohman, Z. , Crano, W. , Siegel, J. , ; Alvaro E. (2013). Attitude ambivalence, friend norms, and adolescent drug use. Prevention Science, Germany: Springer, DOI: 10. 1007/s11121-013-0368-8. Julien, R. M. (2001). A Primer of Drug Action, 4, 88-105, New York: Worth Publishers.Mcgue, M. (1994). Genes, environment and the etiology of Alcoholism. The development of alcohol problems, exploring the biops ychosocial matrix of risk, 26, 1 – 40. Merrill, J. E. , Jennifer, P. , ; Barnett, N. P. (2013). The Way One Thinks Affects the Way One Drinks: Subjective Evaluations of Alcohol Consequences Predict Subsequent Change in Drinking Behaviour,  Psychology of Addictive Behaviours,  27, 42-51. Robbins L. , Edwin, S. , William, A. , Stern, F. , ; Stern M. (1970). College Student Drug Use. American Journal of Psychiatry 126, 12, 1743 – 1751.Rogers, D. (2002). Substance Dependency: Consequences and the Path to Recovery, 8, 78 – 81. Schafer, J. , ; Brown, S. A. (1991). Marijuana and cocaine expectancies and drug use patterns, Journal of Consulting and Clinical Psychology, 59, 558 – 565. Schuster, C. , ; Pickens, R. (1988). AIDS and Intravenous Drug Abuse, Problems of drug dependence 1988, 7, 241 – 252. Strang, J. , ; Farrell, M. (1992). Harm Minimisation for Drug Misusers, 3, 1127–1128, London: Sage Van Hemel-Ruiter, M. E. , DeJong, P. J. , Alberti ne, J. , ; Brian D. Ostafin. 2013). Reward- Related Attentional Biases and Adolescent Substance use: The TRAILS Study. Psychology of Addictive Behaviours, 27, 142-150. Wiers, R. W. , Bartholow, B. D. , Van Den-Wildenberg, E. , Thush, C. , Engels, R. , Sher, K. J. , Grenard, J. , Ames, S. L. , ; Stacy, A. W. (2007). Automatic and controlled processes and the development of addictive behaviors in adolescents: a review and a model. Pharmacol Biochem Behaviour, 86, 263–283. Zinberg, N (1986). Drug, Set, and Setting: The Basis For Controlled Intoxicant Use, 10-11, Yale University Press.

There Are All Kinds Of People - 4680 Words

50 States of Gay There are all kinds of people in this world. People of different races, nationalities, descent, cultures, even sexualities and genders. The people who are not cisexual and/or heterosexual are part of the LGBTQIA community. Since they are still people, one might assume that they have the same rights as everyone else. But that is not the case. Even after all the community has been through, some places around the globe still refuse to give them their rights. But slowly the world is waking up and realizing that people, regardless of sexual orientation and gender identity/expression deserve the same rights as anyone else. The LGBTQIA acronym refers to any lesbian, gay, bisexual, transgender, queer/questioning, intersex, and/or asexual person. I will be using the shortened version throughout this paper, â€Å"LGBT†, but keep in mind that this also includes queer/questioning, intersex, and asexual people. Stereotypes have always been a large part of societal perspective, stereotypes pertaining to sexuality even more so. Sexual stereotypes suggest that all somewhat masculine women are lesbian and that all slightly feminine men are gay. The stereotypical mindset that being gay is just good fashion taste consisting of pastels and the like, a high pitched voice, better manners, more interest in the arts (and none in sports), etc. does not even begin to touch on what being gay actually is. Usually the people who stereotype have no idea what it is like to struggle withShow MoreRelatedThemes In The Outsiders By S. E. Hinton710 Words   |  3 Pagesboth use a theme that relates to people being the same, but growing up or living in a different environment. In To Kill a Mockingbird, the main character, Scout Finch, tells her older brother that there is not more than one kind of people. She tells him that â€Å"there’s just one kind of folks. 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You must find out what kind of data you are looking for. There are a few different types of data to be collected such as descriptive studies or causal studies. Descriptive is the kind of study that asks who what where when and how. The causal studies ask us more they why, they follow the line of thought that if one variable changes then the other willRead MoreUnderstanding the Scientific Field of Social Psychology Essay1565 Words   |  7 Pagesevery aspect of the social behavior of the people and also to understand their mindset and how it impacts their decision making capabilities. Social psychology is much different than other disciplines such as sociology, because it doesn’t use wisdom and anecdotal observations to lay out it facts instead it uses scientific methods and empirical study of social phenomena. Social psychology is always based on research of different subjects using all k inds of scientific methods. These research methods

Youth binge drinking - 1621 Words

To what extent is youth violence, crimes and anti-social behaviour linked to youths binge drinking. Binge drinking can be defined as an excessive consumption of alcohol within a short period of time to get drunk. This essay will focus on how youth violence, crime and anti-social behaviour is linked to youths binge drinking. It is widely known that the youths in United Kingdom start drinking at an early stage of their lives. Talbot and Crabbe (n.d.) state that â€Å"government statistics suggest that†¦ the amount of alcohol consumed by younger adolescents aged 11-13 continues to climb.† Underage drinking is linked to binge drinking as youths are not mature and responsible enough to think of the consequences. BBC News (2003) mentioned that â€Å"A†¦show more content†¦It is also known that regretful sexual activity is a leverage of youths heavy drinking. An article by The Christian Institute (2011) expresses the concern of youths engaging in alcohol-fuelled sex. The article states that â€Å"those binge drinking three or more times a week were over five times m ore likely than non-binge drinkers to have had sex they regretted following alcohol†. It was also suggested that it is time for ministers should have a stricter attitude towards youths binge drinking. The article goes on to declare that the government has failed to control the issue of youths misusing alcohol. Having considered all of the points above, there are arguments about youth violence, crime and anti-social behaviour not relating to binge drinking. It is common for youths to go through a rebellious phase. During the stage of rebellion, crimes will be committed due to peer pressure or low family income. A report by Taylor (2003) claims that street robberies were urged on by the fear of youths being left out and bullied. This suggests that young people are very affected by how they are perceived in the eyes of other individuals which instigate them to commit crime. 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Is Abortion The Right Choice - 2356 Words

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Descriptive Statistics Tabular and Graphical Presentations Free Essays

chapter 2 Chapter 2 Descriptive Statistics: Tabular and Graphical Presentations Learning Objectives 1. Learn how to construct and interpret summarization procedures for qualitative data such as : frequency and relative frequency distributions, bar graphs and pie charts. 2. We will write a custom essay sample on Descriptive Statistics: Tabular and Graphical Presentations or any similar topic only for you Order Now Learn how to construct and interpret tabular summarization procedures for quantitative data such as: frequency and relative frequency distributions, cumulative frequency and cumulative relative frequency distributions. . Learn how to construct a dot plot, a histogram, and an ogive as graphical summaries of quantitative data. 4. Learn how the shape of a data distribution is revealed by a histogram. Learn how to recognize when a data distribution is negatively skewed, symmetric, and positively skewed. 5. Be able to use and interpret the exploratory data analysis technique of a stem-and-leaf display. 6. Learn how to construct and interpret cross tabulations and scatter diagrams of bivariate data. Solutions: 1. |Class |Frequency |Relative Frequency | |A |60 |60/120 = 0. 50 | |B | 24 |24/120 = 0. 20 | |C | 36 |36/120 = 0. 30 | | |120 | 1. 00 | 2. a. 1 – (. 22 + . 18 + . 40) = . 20 b.. 20(200) = 40 c/d. Class |Frequency |Percent Frequency | |A |. 22(200) = 44 | 22 | |B |. 18(200) = 36 | 18 | |C |. 40(200) = 80 | 40 | |D |. 20(200) = 40 | 20 | |Total |200 |100 | 3. a. 360 ° x 58/120 = 174 ° b. 360 ° x 42/120 = 126 ° c. [pic] d. [pic] 4. a. The data are qualitative. b. | |Percent Frequency | |Newspaper |Frequency | | |Liberty Times |24 |48 | |China Times |15 |30 | |United Daily News |7 |14 | |Apple Daily |4 |8 | |Total: |50 |100 | c. [pic] [pic] d. Liberty Times has the largest market share. China Times is second. 5. a. |Name |Frequency |Relative Frequency |Percent Frequency | |Chan |10 |. 200 |20. 0% | |Chang |7 |. 140 |14. 0% | |Lee |8 |. 160 |16. 0% | |Liu |7 |. 140 |14. 0% | |Wang |12 |. 240 |24. % | |Young |6 |. 120 |12. 0% | | |50 |1. 000 |100. 0% | b. [pic] c. Chan. 200 x 360 = 72. 0( Chang. 140 x 360 = 50. 4( Lee. 160 x 360 = 58. 6( Liu. 140 x 360 = 50. 4( Wang. 240 x 360 = 86. 4( Young. 120 x 360 = 43. 2( [pic] d. Most common: Wang, Chan, and Lee 6. a. |Book |Frequency |Percent Frequency | |7 Habits |10 | |16. 6 | | |Millionaire |16 | |26. 67 | | |Motley |9 | |15. 00 | | |Dad |13 | |21. 67 | | |WSJ Guide |6 | |10. 00 | | |Other |6 | |10. 00 | | |Total: |60 | |100. 00 | | The Ernst Young Tax Guide 2000 with a frequency of 3, Investing for Dummies with a frequency of 2, and What Color is Your Parachute? 2000 with a frequency of 1 are grouped in the â€Å"Other† category. b. The rank order from first to fifth is: Millionaire, Dad, 7 Habits, Motley, and WSJ Guide. c. The percent of sales represented by The Millionaire Next Door and Rich Dad, Poor Dad is 48. 33%. 7. |Rating |Frequency |Relative Frequency | |Outstanding |19 |0. 8 | |Very Good |13 |0. 26 | |Good |10 |0. 20 | |Average | 6 |0. 12 | |Poor | 2 |0. 04 | | |50 |1. 00 | Management should be pleased with these results. 64% of the ratings are very good to outstanding. 84% of the ratings are good or better. Comparing these ratings with previous results will show whether or not the restaurant is making improvements in its ratings of food quality. 8. a. |Position |Frequency |Relative Frequency | |Pitcher |17 |0. 309 | |Catcher | 4 |0. 073 | |1st Base | 5 |0. 091 | |2nd Base | 4 |0. 073 | |3rd Base | 2 |0. 36 | |Shortstop | 5 |0. 091 | |Left Field | 6 |0. 109 | |Center Field | 5 |0. 091 | |Right Field | 7 |0. 127 | | |55 |1. 000 | b. Pitchers (Almost 31%) c. 3rd Base (3 – 4%) d. Right Field (Almost 13%) e. Infielders (16 or 29. 1%) to Outfielders (18 or 32. 7%) 9. a/b. Starting Time | Frequency |Percent Frequency | |7:00 |3 | |15 | | |7:30 |4 | |20 | | |8:00 |4 | |20 | | |8:30 |7 | |35 | | |9:00 |2 | |10 | | | |20 | |100 | | c. Bar Graph [pic] d. [pic] . The most preferred starting time is 8:30 a. m.. Starting times of 7:30 and 8:00 a. m. are next. 10. a. The data refer to quality levels from 1 â€Å"Not at all Satisfied† to 7 â€Å"Extremely Satisfied. † b. |Rating |F requency |Relative Frequency | |3 |2 | 0. 03 | |4 |4 | 0. 07 | |5 |12 | 0. 20 | |6 |24 | 0. 40 | |7 |18 | 0. 0 | | |60 | 1. 00 | c. Bar Graph [pic] d. The survey data indicate a high quality of service by the financial consultant. The most common ratings are 6 and 7 (70%) where 7 is extremely satisfied. Only 2 ratings are below the middle scale value of 4. There are no â€Å"Not at all Satisfied† ratings. 11. |Class |Frequency |Relative Frequency |Percent Frequency | | | | | | |12-14 |2 |0. 50 |5. 0 | |15-17 | 8 |0. 200 | 20. 0 | |18-20 |11 |0. 275 | 27. 5 | |21-23 |10 |0. 250 | 25. 5 | |24-26 | 9 |0. 225 | 22. 5 | |Total |40 |1. 000 |100. | 12. |Class |Cumulative Frequency |Cumulative Relative Frequency | |less than or equal to 19 |10 | . 20 | |less than or equal to 29 |24 | . 48 | |less than or equal to 39 |41 | . 82 | |less than or equal to 49 |48 | . 6 | |less than or equal to 59 |50 |1. 00 | 13. [pic] [pic] 14. a. [pic] b/c. |Class |Frequency |Percent Frequency | | 6. 0 – 7. 9 |4 | 20 | | 8. 0 – 9. 9 | 2 | 10 | |10. 0 – 11. 9 | 8 | 40 | |12. 0 – 13. 9 | 3 | 15 | |14. 0 – 15. | 3 | 15 | | |20 |100 | 15. a/b. |Waiting Time |Frequency |Relative Frequency | |0 – 4 |4 |0. 20 | |5 – 9 | 8 |0. 40 | |10 – 14 | 5 |0. 25 | |15 – 19 | 2 |0. 10 | |20 – 24 | 1 |0. 5 | |Totals |20 |1. 00 | c/d. |Waiting Time |Cumulative Frequency |Cumulative Relative Frequency | |Less than or equal to 4 |4 |0. 20 | |Less than or equal to 9 |12 |0. 60 | |Less than or equal to 14 |17 |0. 5 | |Less than or equal to 19 |19 |0. 95 | |Less than or equal to 24 |20 |1. 00 | e. 12/20 = 0. 60 16. a. The histogram is shown below. [pic] The histogram clearly shows that the annual household incomes are skewed to the right. And, of course, if annual household incomes are skewed to the right, so are annual incomes. This makes sense because the vast majority of annual incomes are less than NT$1,000,000. But, there are a few individuals with very large incomes. b. The histogram for the age is given. [pic] The histogram shows that the distribution of age is skewed to the left. This is to be expected. It is our experience that there are frequently a few very low ages causing such a pattern to appear. c. The histogram for the data in Exercise 11 is given. d. [pic] e. This histogram is skewed to the left slightly, but we would probably classify it as roughly symmetric. 17. a. |Amount (NT$ ‘000) |Frequency |Relative Frequency | |Less than 56 |3 |. 2 | |56-75 |5 |. 20 | |76-95 |11 |. 44 | |96-115 |4 |. 16 | |116-135 |1 |. 04 | |136 and more | 1 |. 04 | | |25 |1. 00 | b. Histogram [pic] The distribution has a roughly symmetric shape. c. The largest group spends NT$76-NT$95 per year on books and magazines. There are more in the NT$56 to NT$75 range than in the NT$96 to NT$115 range. 18. a. Lowest salary: NT$29,300 Highest salary: NT$37,800 b. |Salary (NT$100s) |Frequency |Relative |Percent Frequency | | | |Frequency | | |293-307 |4 |0. 09 |9 | |308-322 |5 |0. 11 |11 | |323-337 |9 |0. 0 |20 | |338-352 |17 |0. 38 |38 | |353-367 |7 |0. 16 |16 | |368-382 |3 |0. 07 |7 | |Total |45 |1. 00 |100 | c. Proportion NT$33,700 or less: 18/45. d. Percentage more than NT$35,200: 10/45 [pic] e. The distribution is skewed slightly to the left, but is roughly symmetric. 19. a/b. Number |Frequency |Relative Frequency | |140 – 149 | 2 |0. 10 | |150 – 159 | 7 |0. 35 | |160 – 169 | 3 |0. 15 | |170 – 179 | 6 |0. 30 | |180 – 189 | 1 |0. 05 | |190 – 199 | 1 |0. 05 | |Totals |20 |1. 0 | c/d. |Number |Cumulative Frequency |Cumulative Relative Frequency | |Less than or equal to 149 | 2 |0. 10 | |Less tha n or equal to 159 | 9 |0. 45 | |Less than or equal to 169 |12 |0. 60 | |Less than or equal to 179 |18 |0. 0 | |Less than or equal to 189 |19 |0. 95 | |Less than or equal to 199 |20 |1. 00 | e. [pic] 20. a. The percentage of people 39 or less is 12. 2 + 14. 2 + 17. 1 + 16. 2 = 59. 7. b. The percentage of the population over 39 years old is 16. 3 + 10. 9 + 6. 7 + 4. 7 + 1. 7 = 40. 3 c. The percentage of the population that is between 20 and 59 years old inclusively is 17. 1 + 16. 2 + 16. 3 + 10. = 60. 5 d. The percentage less than 30 years old is 12. 2 + 14. 2 + 17. 1 = 43. 5. So there are (. 435) (22,689,122) = 9,869,768. 07 people less than 30 years old. e. An estimate of the number of retired people is (. 047 + . 017) (22,689,122) = 1,452,103. 81 21. a/b. |Computer Usage | |Relative Frequency | |(Hours) |Frequency | | |0. 0 |- |2. 9 |5 |0. 10 | |3. 0 |- |5. 9 |28 |0. 56 | |6. 0 |- |8. |8 |0. 16 | |9. 0 |- |11. 9 |6 |0. 12 | |12. 0 |- |14. 9 |3 |0. 06 | | |Total |50 |1. 00 | c. [pic ] d. [pic] e. The majority of the computer users are in the 3 to 6 hour range. Usage is somewhat skewed toward the right with 3 users in the 12 to 15 hour range. 22. |5 |7 8 | |6 |4 5 8 | |7 |0 2 2 5 5 6 8 | 8 |0 2 3 5 | 23. Leaf Unit = 0. 1 |6 |3 | |7 |5 5 7 | |8 |1 3 4 8 | |9 |3 6 | |10 |0 4 5 | |11 |3 | 24. Leaf Unit = 10 |11 |6 | |12 |0 2 | |13 |0 6 7 | |14 |2 2 7 | |15 |5 | |16 |0 2 8 | 17 |0 2 3 | 25. | 9 |8 9 | |10 |2 4 6 6 | |11 |4 5 7 8 8 9 | |12 |2 4 5 7 | |13 |1 2 | |14 |4 | |15 |1 | 26. a. 100 shares at $50 per share |1 |0 3 7 7 | |2 |4 5 5 | |3 |0 0 5 5 9 | |4 |0 0 0 5 5 8 | |5 |0 0 0 4 5 5 | This stem-and-leaf display shows that the trading prices are closely grouped together. Rotating the stem-and-leaf display counter clockwise shows a histogram that is slightly skewed to the left but is roughly symmetric. b. 500 shares traded online at $50 per share. |0 |5 7 | |1 |0 1 1 3 4 | |1 |5 5 5 8 | |2 |0 0 0 0 0 0 | |2 |5 5 | |3 |0 0 0 | |3 |6 | 4 | | |4 | | |5 | | |5 | | |6 |3 | This stretched stem-and-leaf display shows that the distribution of online trading prices for most of the brokers for 500 shares are lower than the trading prices for broker assisted trades of 100 shares. There are a couple of outliers. York Securities charges $36 for an online trade and Investors National charges much more than the other brokers: $62. 50 for an online trade. 27. 4 |1 3 6 6 7 | |5 |0 0 3 8 9 | |6 |0 1 1 4 4 5 7 7 9 | |7 |0 0 0 1 3 4 4 5 5 6 6 6 7 8 8 | |8 |0 1 1 3 4 4 5 7 7 8 9 | |9 |0 2 2 7 | or |4 |1 3 | |4 |6 6 7 | |5 |0 0 3 | |5 |8 9 | 6 |0 1 1 4 4 | |6 |5 7 7 9 9 | |7 |0 0 0 1 3 4 4 | |7 |5 5 6 6 6 7 8 8 | |8 |0 1 1 3 4 4 | |8 |5 7 7 8 9 | |9 |0 2 2 | |9 |7 | 28. a. |0 |5 8 | |1 |1 1 3 3 4 4 | |1 |5 6 7 8 9 9 | |2 |2 3 3 3 5 5 | |2 |6 8 | |3 | | 3 |6 7 7 9 | |4 |0 | |4 |7 8 | |5 | | |5 | | |6 |0 | b. |2000 P/E Forecast | |Percent Frequency | | |Frequency | | |5 – 9 |2 |6. 7 | | |10 – 14 |6 |20. 0 | | |15 – 19 |6 |20. 0 | | |20 – 24 |6 |20. | | |25 – 29 |2 |6. 7 | | |30 – 34 |0 |0. 0 | | |35 – 39 |4 |13. 3 | | |40 – 44 |1 |3. 3 | | |45 – 49 |2 |6. 7 | | |50 – 54 |0 |0. 0 | | |55 – 59 |0 |0. 0 | | |60 – 64 |1 |3. 3 | | |Total |30 |100. 0 | | 29. a. [pic] b. [pic] c. [pic] d. Category A values for x are always associated with category 1 values for y. Category B values for x are usually associated with category 1 values for y. Category C values for x are usually associated with category 2 values for y. 30. a. [pic] b. There is a negative relationship between x and y; y decreases as x increases. 31. a. Row Percentages: | |Household Income (NT$ ‘000) | | |Age |Under 999 |1,000-1,499 |1,500-1,999 |2,000-2,499 |2,500-2,999 |3,000 or more |Total | |Under 34 |27. 6 |30. 54 |21. 01 |12. 99 |4. 93 |2. 76 |100. 00 | |35-44 |20. 90 |31. 32 |21. 49 |10. 48 |8. 79 |7. 03 |100. 00 | |45-54 |16. 00 |29. 17 |19. 24 |19. 87 |6. 83 |8. 88 |100. 00 | |55-64 |23. 73 |19. 26 |20. 01 |14. 46 |8. 81 |13. 73 |100. 00 | |65 or more |70. 57 |18. 37 |4. 42 |2. 4 |0. 74 |2. 96 |100. 00 | |Total |27. 70 |27. 32 |18. 27 |13. 05 |6. 51 |7. 15 |100. 00 | There are seven percent frequency distributions in this table with row percentages. The first six give the percent frequency dis tribution of income for each age level. The total row provides an overall percent frequency distribution for household income. Both of the two rows (age 35-44 and age 55- 64) have more percentage in the cells and descended in order of larger income. The second row is the percent frequency distribution for households headed by age 35-44. The fourth row is the percent frequency distribution for households headed by age 55-64. b. The percentage of heads of households by age 35-44 earning NT$2,500,000 or more is 8. 79% + 7. 03% = 15. 82%. The percentage of heads of households by age 55-64 earning $75,000 or more is 8. 81% + 13. 73% = 22. 54%. c. The percent frequency histograms are shown below. [pic] No. The histogram can not tell us any relationship between household income and age. 32. a. Column Percentages: |Household Income ($1000s) | | |Education Level |Under 24. 9 |25. 0-49. 9 |50. 0-74. 9 |75. 0-99. 9 |100 or More |Total | |Not H. S. Graduate |32. 70 |14. 82 |8. 27 |5. 02 |2. 53 |15. 86 | |H. S. Graduate |35. 74 |35. 56 |31. 48 |25. 39 |14. 47 |30. 78 | |Some College |21. 17 |29. 77 |30. 25 |29. 2 |22. 26 |26. 37 | |Bachelor’s Degree |7. 53 |14. 43 |20. 56 |25. 03 |33. 88 |17. 52 | |Beyond Bach. Deg. |2. 86 |5. 42 |9. 44 |14. 74 |26. 86 |9. 48 | |Total |100. 00 |100. 00 |100. 00 |100. 00 |100. 00 |100. 00 | There are six percent frequency distributions in this table of column percentages. The first five columns give the percent frequency distributions for each income level. The percent frequency distribution in the â€Å"Total† column gives the overall percent frequency distributions for educational level. From that percent frequency distribution we see that 15. 86% of the heads of households did not graduate from high school. b. The column percentages show that 26. 86% of households earning over $100,000 were headed by persons having schooling beyond a bachelor’s degree. The row percentages show that 39. 72% of the households headed by persons with schooling beyond a bachelor’s degree earned $100,000 or more. These percentages are different because they came from different percent frequency distributions. c. Compare the â€Å"under 24. 9† percent frequency distributions to the â€Å"Total† percent frequency distributions. We see that for this low income level the percentage with lower levels of education is lower than for the overall population and the percentage with higher levels of education is higher than for the overall population. Compare the â€Å"100 or more† percent frequency distribution to â€Å"Total† percent frequency distribution. We see that for this high income level the percentage with lower levels of education is lower than for the overall population and the percentage with higher levels of education is higher than for the overall population. From the comparisons here it is clear that there is a positive relationship between household incomes and the education level of the head of the household. 33. a. The crosstabulation of condition of the greens by gender is below. | |Green Condition | | |Gender |Too Fast |Fine |Total | |Male |35 | 65 |100 | |Female |40 | 60 |100 | |Total |75 |125 |200 | The female golfers have the highest percentage saying the greens are too fast: 40%. b. 10% of the women think the greens are too fast. 20% of the men think the greens are too fast. So, for the low handicappers, the men have a higher percentage who think the greens are too fast. c. 43% of the woman think the greens are too fast. 50% of the men think the greens are too fast. So, for the high handicappers, the men have a higher percentage who think the greens are too fast. . This is an example of Simpson’s Paradox. At each handicap level a smaller percentage of the women think the greens are too fast. But, when the crosstabulations are aggregated, the result is reversed and we find a higher percentage of women who think the greens are too fast. The hidden variable explaining the reversal is handicap level. Fewer people with low handicaps think the greens are too fast, and there are more men with low handicaps than women. 34. a. | |EPS Rating | | | |Sales/Margins/ROE |0-19 |20-39 |40-59 |60-79 |80-100 |Total | |A | | | |1 |8 |9 | |B | |1 |4 |5 |2 |12 | |C |1 | |1 |2 |3 |7 | |D |3 |1 | |1 | |5 | |E | |2 |1 | | |3 | |Total |4 |4 |6 |9 |13 |36 | b. | | |EPS Rating | | | |Sales/Margins/ROE |0-19 |20-39 |40-59 |60-79 |80-100 |Total | |A | | | |11. 11 |88. 89 |100 | |B | |8. 33 |33. 33 |41. 67 |16. 67 100 | |C |14. 29 | |14. 29 |28. 57 |42. 86 |100 | |D |60. 00 |20. 00 | |20. 00 | |100 | |E | |66. 67 |33. 33 | | |100 | Higher EPS ratings seem to be associated with higher ratings on Sales/Margins/ROE. Of those companies with an â€Å"A† rating on Sales/Margins/ROE, 88. 89% of them had an EPS Rating of 80 or higher. Of the 8 companies with a â€Å"D† or â€Å"E† rating on Sales/Margins/ROE, only 1 had an EPS rating above 60. 35. a. | |Industry Group Relative Strength | | | |Sales/Margins/ROE |A |B |C |D |E |Total | |A |1 |2 |2 |4 | |9 | |B |1 |5 |2 |3 |1 |12 | |C |1 |3 | |2 |1 |7 | |D |1 | |1 |1 |2 |5 | |E | |1 |2 | | |3 | |Total |4 |11 |7 |10 | 4 |36 | | | | | | | | | b/c. The frequency distributions for the Sales/Margins/ROE data is in the rightmost column of the crosstabulation. The frequency distribution for the Industry Group Relative Strength data is in the bottom row of the crosstabulation. d. Once the crosstabulation is complete, the individual frequency distributions are available in the margins. 36. a. [pic] b. One might expect stocks with higher EPS ratings to show greater relative price strength. However, the scatter diagram using this data does not support such a relationship. The scatter diagram appears similar to the one showing â€Å"No Apparent Relationship† in the text. 37. a. The crosstabulation is shown below: | |Speed |   | |Position |4-4. 49 |4. 5-4. 99 |5-5. 49 |5. 5-5. 9 |Grand Total | |Guard | | |12 |1 |13 | |Offensive tackle | |2 |7 |3 |12 | |Wide receiver |6 |9 | | |15 | |Grand Total |6 |11 |19 |4 |40 | b. There appears to be a relationship between Position and Speed; wide receivers had faster speeds than offensive tackles and guards. c. The scatter diagram is shown below: [pic] d. There appears to be a relationship between S peed and Rating; slower speeds appear to be associated with lower ratings. In other words,, prospects with faster speeds tend to be rated higher than prospects with slower speeds. 38. a. |Vehicle |Frequency |Percent Frequency | F-Series |17 |34 | |Silverado |12 |24 | |Taurus |8 |16 | |Camry |7 |14 | |Accord |6 |12 | |Total |50 |100 | b. The two top selling vehicles are the Ford F-Series Pickup and the Chevrolet Silverado. c. 39. a/b. |Industry |Frequency |Percent Frequency | |Beverage |2 |10 | |Chemicals | 3 | 15 | |Electronics | 6 | 30 | |Food | 7 | 35 | |Aerospace | 2 | 10 | |Totals: |20 |100 | . 40. a. Response |Frequency |Percent Frequency | |Accuracy |16 |16 | |Approach Shots |3 |3 | |Mental Approach |17 |17 | |Power |8 |8 | |Practice |15 |15 | |Putting |10 |10 | |Short Game |24 |24 | |Strategic Decisions | 7 | 7 | |Total |100 |100 | b. Poor short game, poor mental approach, lack of accuracy, and limited practice. 41. a/b/c/d. Book Value | |Relative Frequency |Cumulative Freque ncy |Cumulative | |per Share |Frequency | | |Relative Frequency | |0. 00-5. 99 | 3 |0. 10 | 3 |0. 10 | |6. 00-11. 99 | 15 |0. 50 |18 |0. 60 | |12. 00-17. 99 | 9 |0. 30 |27 |0. 90 | |18. 00-23. 99 | 2 |0. 07 |29 |0. 97 | |24. 00-29. 99 | 0 |0. 00 |29 |0. 7 | |30. 00-35. 99 | 1 |0. 03 |30 |1. 00 | |Total |30 |1. 00 | | | e. The histogram shown below shows that the distribution of most of the book values is roughly symmetric. However, there is one outlier (General Motors). 42. a. |Closing Price |Frequency |Relative Frequency | |0 – 9 7/8 |9 |0. 225 | |10 – 19 7/8 |10 |0. 250 | |20 – 29 7/8 | 5 |0. 25 | |30 – 39 7/8 |11 |0. 275 | |40 – 49 7/8 | 2 |0. 050 | |50 – 59 7/8 | 2 |0. 050 | |60 – 69 7/8 | 0 |0. 000 | |70 – 79 7/8 | 1 |0. 025 | |Totals |40 |1. 000 | b. |Closing Price |Cumulative Frequency |Cumulative Relative Frequency | |Less than or equal to 9 7/8 |9 |0. 25 | |Less than or equal to 19 7/8 |19 |0. 475 | |Less than or equal to 29 7/8 |24 |0. 600 | |Less than or equal to 39 7/8 |35 |0. 875 | |Less than or equal to 49 7/8 |37 |0. 925 | |Less than or equal to 59 7/8 |39 |0. 975 | |Less than or equal to 69 7/8 |39 |0. 75 | |Less than or equal to 79 7/8 |40 |1. 000 | c. [pic] d. Over 87% of common stocks trade for less than $40 a share and 60% trade for less than $30 per share. 43. a. | | |Relative Frequency | |Exchange |Frequency | | |American |3 |0. 15 | |New York |2 |0. 10 | |Over the Counter |15 |0. 75 | | |20 |1. 00 | b. Earnings Per Share | |Relative Frequency | | |Frequency | | |0. 00 – 0. 19 |7 |0. 35 | |0. 20 – 0. 39 |7 |0. 35 | |0. 40 – 0. 59 |1 |0. 05 | |0. 60 – 0. 79 |3 |0. 15 | |0. 80 – 0. 99 |2 |0. 10 | | |20 |1. 00 | Seventy percent of the shadow stocks have earnings per share less than $0. 40. It looks like low EPS should be expected for shadow stocks. | | | |Price-Earning Ratio | |Relative Frequency | | |Frequency | | |0. 00 – 9. 9 |3 |0. 15 | |10. 0 – 19. 9 |7 |0. 35 | |20. 0 – 29. 9 |4 |0. 20 | |30. 0 – 39. 9 |3 |0. 15 | |40. 0 – 49. 9 |2 |0. 10 | |50. 0 – 59. 9 |1 |0. 05 | | |20 |1. 00 | P-E Ratios vary considerably, but there is a significant cluster in the 10 – 19. 9 range. 44. | | |Relative Frequency | |Income ($) |Frequency | | |18,000-21,999 |13 |0. 255 | |22,000-25,999 |20 |0. 392 | |26,000-29,999 |12 |0. 235 | |30,000-33,999 |4 |0. 078 | |34,000-37,999 |2 |0. 039 | |Total |51 |1. 000 | 45. a. 0 |8 9 | |1 |0 2 2 2 3 4 4 4 | |1 |5 5 6 6 6 6 7 7 8 8 8 8 9 9 9 | |2 |0 1 2 2 2 3 4 4 4 | |2 |5 6 8 | |3 |0 1 3 | b/c/d. |Number Answered Correctly | |Relative Frequency |Cumulative Frequency | | |Frequency | | | |5 – 9 |2 |0. 50 |2 | |10 – 14 | 8 |0. 200 |10 | |15 – 19 |15 |0. 375 |25 | |20 – 24 | 9 |0. 225 |34 | |25 – 29 | 3 |0. 075 |37 | |30 – 34 | 3 |0. 075 |40 | |Totals |40 |1. 000 | | e. Relatively few of the students (25%) were able to answer 1/2 or more of the questions correctly. The data seem to support the Joint Council on Economic Education’s claim. However, the degree of difficulty of the questions needs to be taken into account before reaching a final conclusion. 46. a/b. [pic] c. It is clear that the range of low temperatures is below the range of high temperatures. Looking at the stem-and-leaf displays side by side, it appears that the range of low temperatures is about 20 degrees below the range of high temperatures. d. There are two stems showing high temperatures of 80 degrees or higher. They show 8 cities with high temperatures of 80 degrees or higher. e. Frequency |Temperature |High Temp. |Low. Temp. |30-39 |0 |1 | |40-49 |0 |3 | |50-59 |1 |10 | |60-69 |7 |2 | |70-79 |4 |4 | |80-89 |5 |0 | |90-99 |3 |0 | |Total |20 |20 | 47. a. b. There is clearly a positive relationship between high and low temperature for cities. As one goes up so does the other. 48. a. | |Satisfaction Score | | | |Occupation |30-39 |40-49 |50-59 |60-69 |70-79 |80-89 |Tot al | |Cabinetmaker | | |2 |4 |3 |1 |10 | |Lawyer |1 |5 |2 |1 |1 | |10 | |Physical Therapist | | |5 |2 |1 |2 |10 | |Systems Analyst | |2 |1 |4 |3 | |10 | |Total |1 |7 |10 |11 |8 |3 |40 | b. | | |Satisfaction Score | | | |Occupation |30-39 |40-49 |50-59 |60-69 |70-79 |80-89 |Total | |Cabinetmaker | | |20 |40 |30 |10 |100 | |Lawyer |10 |50 |20 |10 |10 | |100 | |Physical Therapist | | |50 |20 |10 |20 |100 | Systems Analyst | |20 |10 |40 |30 | |100 | c. Each row of the percent crosstabulation shows a percent frequency distribution for an occupation. Cabinet makers seem to have the higher job satisfaction scores while lawyers seem to have the lowest. Fifty percent of the physical therapists have mediocre scores but the rest are rather high. 49. a. [pic]b. There appears to be a positive relationship between number of employees and revenue. As the number of employees increases, annual revenue increases. 50. a. | | |Fuel Type | | | |Year Constructed |Elec |Nat. Gas |Oil |Propane |Other |Total | |1973 or before | 40 |183 |12 |5 | 7 |247 | |1974-1979 | 24 | 26 | 2 |2 | 0 | 54 | |1980-1986 | 37 | 38 | 1 |0 | 6 | 82 | |1987-1991 | 48 | 70 | 2 |0 | 1 |121 | |Total |149 |317 |17 |7 |14 |504 | b. |Year Constructed |Frequency |Fuel Type |Frequency | |1973 or before |247 | Electricity |149 | |1974-1979 | 54 | Nat. Gas |317 | |1980-1986 | 82 | Oil | 17 | |1987-1991 |121 | Propane | 7 | |Total |504 | Other | 14 | | | |Total |504 | c. Crosstabulation of Column Percentages | | |Fuel Type | | |Year Constructed |Elec |Nat. Gas |Oil |Propane |Other | |1973 or before | 26. 9 | 57. 7 | 70. 5 | 71. 4 | 50. 0 | |1974-1979 | 16. 1 | 8. 2 | 11. 8 | 28. 6 | 0. 0 | |1980-1986 | 24. 8 | 12. 0 | 5. 9 | 0. 0 | 42. 9 | |1987-1991 | 32. 2 | 22. 1 | 11. 8 | 0. 0 | 7. 1 | |Total |100. 0 |100. 0 |100. 0 |100. 0 |100. 0 | d. Crosstabulation of row percentages. | |Fuel Type | | | |Year Constructed |Elec |Nat. Gas |Oil |Propane |Other |Total | |1973 or before |16. 2 |74. 1 |4. 9 |2. 0 |2. 8 |100. 0 | |1974-1979 |44. 5 |48. 1 |3. 7 |3. 7 |0. 0 |100. 0 | |1980-1986 |45. 1 |46. 4 |1. 2 |0. 0 |7. 3 |100. 0 | |1987-1991 |39. 7 |57. 8 |1. 7 |0. 0 |0. 8 |100. 0 | e. Observations from the column percentages crosstabulation For those buildings using electricity, the percentage has not changed greatly over the years. For the buildings using natural gas, the majority were constructed in 1973 or before; the second largest percentage was constructed in 1987-1991. Most of the buildings using oil were constructed in 1973 or before. All of the buildings using propane are older. Observations from the row percentages crosstabulation Most of the buildings in the CGE service area use electricity or natural gas. In the period 1973 or before most used natural gas. From 1974-1986, it is fairly evenly divided between electricity and natural gas. Since 1987 almost all new buildings are using electricity or natural gas with natural gas being the clear leader. 51. a. Crosstabulation for stockholder’s equity and profit. | |Profits ($000) | | | |Stockholders’ Equity ($000) |0-200 |200-400 |400-600 |600-800 |800-1000 |1000-1200 |Total | |0-1200 |10 |1 | | | |1 |12 | |1200-2400 |4 |10 | | |2 | |16 | |2400-3600 |4 |3 |3 |1 |1 |1 |13 | |3600-4800 | | | | |1 |2 |3 | |4800-6000 | |2 |3 |1 | | |6 | |Total |1 8 |16 |6 |2 |4 |4 |50 | b. Crosstabulation of Row Percentages. | | |Profits ($000) | | | |Stockholders’ Equity ($1000s) |0-200 |200-400 |400-600 |600-800 |800-1000 |1000-1200 |Total | |0-1200 |83. 33 |8. 33 |0. 00 |0. 00 |0. 00 |8. 33 |100 | |1200-2400 |25. 00 |62. 50 |0. 00 |0. 00 |12. 50 |0. 0 |100 | |2400-3600 |30. 77 |23. 08 |23. 08 |7. 69 |7. 69 |7. 69 |100 | |3600-4800 | |0. 00 |0. 00 |0. 00 |33. 33 |66. 67 |100 | |4800-6000 |0. 00 |33. 33 |50. 00 |16. 67 |0. 00 |0. 00 |100 | c. Stockholder’s equity and profit seem to be related. As profit goes up, stockholder’s equity goes up. The relationship, however, is not very strong. 52. a. Crosstabulation of market value and profit. | |Profit ($1000s) | | | |Market Value ($1000s) |0-300 |300-600 |600-900 |900-1200 |Total | |0-8000 |23 |4 | | |27 | |8000-16000 |4 |4 |2 |2 |12 | |16000-24000 | |2 |1 |1 |4 | |24000-32000 | |1 |2 |1 |4 | |32000-40000 | |2 |1 | |3 | |Total |27 |13 |6 |4 |50 | b. Crosstabulation of Row P ercentages. | | |Profit ($1000s) | | | |Market Value ($1000s) |0-300 |300-600 |600-900 |900-1200 |Total | |0-8000 |85. 19 |14. 81 |0. 00 |0. 00 |100 | |8000-16000 |33. 33 |33. 33 |16. 67 |16. 67 |100 | |16000-24000 |0. 00 |50. 00 |25. 00 |25. 0 |100 | |24000-32000 |0. 00 |25. 00 |50. 00 |25. 00 |100 | |32000-40000 |0. 00 |66. 67 |33. 33 |0. 00 |100 | c. There appears to be a positive relationship between Profit and Market Value. As profit goes up, Market Value goes up. 53. a. Scatter diagram of Profit vs. Stockholder’s Equity. [pic] b. Profit and Stockholder’s Equity appear to be positively related. 54. a. Scatter diagram of Market Value and Stockholder’s Equity. [pic] b. There is a positive relationship between Market Value and Stockholder’s Equity. ———————– [pic] [pic] [pic] How to cite Descriptive Statistics: Tabular and Graphical Presentations, Essays