STAT303: Secs 102 and 103Summer I 2001Exam #4Form AInstructor: Julie Hagen Carroll1. Don’t EVEN open this until you are told to do so.2. Be sure to mark your section number and your test form (A, B, C or D) on the scantron!3. Sign your name where indicated on your scantron and write your section number, seat number andcomputer number beside it. You will get your scantrons back tomorrow in class. You may keep thisexam.4. There are 20 multiple-choice questions on this exam, each worth 5 points. There is partial credit. Pleasemark your answers clearly on the scantron. Multiple marks will be counted wrong.5. You will have 60 minutes to finish this exam.6. If you are caught cheating or helping someone to cheat on this exam, you both will receive a grade ofzero on the exam. You must work alone.7. This exam is worth 100 points, and will constitute 20% of your final grade.8. Good luck! This is IT!1STAT303: 102 and 103 Exam #4, Form A Summer 20011. Suppose I want to know whether ‘summer school’has an effect on the class average. If I have theclass averages for the last 3 semesters (fall, springand summer), how should I compare them, i.e.,what type of test should I run? Note: since eachclass has at least 50 students, I can assume thatthe means are normally distributed.A. One way ANOVA on the multiple means:fall, spring and summer.B. Case 9 since the sample is large and thereare no other assumptions.C. Case 10, pairing the grades by major.D. Case 11 since I want to know if summerschool and grades are independent or not.E. Chi-squared test since we have 3 propor-tions: percent passing in fall, spring andsummer.2. What does the residual plot above tells us?A. The residuals are linear; therefore, normallydistributed.B. The linear relationship between Part No.(order) and Length (of part) is valid.C. The variance of the residuals is not con-stant.D. The relationship between Part No. (order)and Length (of part) is not simple linear.E. The residual plot shows no problems.3. What does ‘statistical significance’ mean for aOne-way ANOVA F -test?A. It means that true (population) means aresignificant.B. It means that the true means are equal.C. It means that the group effect on the meansis significant.D. It means that the true slope is 0.E. None of the above are true.Survival Time of Untreatable CancerVariable | Obs Mean Std. Dev.---------+------------------------------Vit C | 30 279.8 309.3703No Vit C | 30 32.6 18.32767---------+------------------------------combined | 60 156.2Ho: mu(x) - mu(y) = 0 (unequal variances)t = 4.37 with 29.2 d.f.Pr > |t| = 0.000195% CI = (131.512,362.888)4. The output above is a 2-sample t-test for testingwhether taking vitamin C (or not) has an effecton (makes a difference in) the survival time ofuntreatable cancer. What is the correct conclu-sion? Note: the p-value = 0.0001.A. We must run an ANOVA to determine theeffect.B. We can conclude at the 1% level that tak-ing vitamin C does make a difference in thesurvival time.C. We can conclude at the 1% level that tak-ing vitamin C does make a difference in thesurvival rate.D. We can conclude at the 10% level only thattaking vitamin C does make a difference inthe survival rate.E. We can conclude that there is only a 0.0001probability of surviving cancer.5. Given the following 90, 95, and 99% confidenceintervals for the true population slope, β1: (-1.28,1.19), (-1.55,1.46), (-2.04,2.13), what is thebest statement of the p-value for testing H0:β1= 0 vs. HA: β16= 0?A. p-value > 0.10B. 0.10 > p-value > 0.05C. 0.05 > p-value > 0.01D. p-value < 0.01E. The slope must be positive, so there is anerror in the confidence intervals, and the p-value cannot be determined.6. What is the advantage of the paired t test overthe other 2-sample t tests?A. It uses less data.B. It has less variability.C. It has more degresses of freedom.D. All of the above are true.E. Exactly two of the above are true.2STAT303: 102 and 103 Exam #4, Form A Summer 20017. Which of the following best describes the as-sumptions for the Chi-squared test in a contin-gency table?A. Each sample size must be at least 30.B. The variances must be equal.C. The means must be equal.D. The proportions must be equal.E. Each count must be at least 5.--------------------------------------------------agew | Coef. Std.Err. t P>|t| [95% C. I.]------+-------------------------------------------ageh | .91124 .02585 35.249 0.000 .8602 .9623_cons | 1.5740 1.1501 1.369 0.173 -.697 3.8446--------------------------------------------------8. Which of the following would be a valid state-ment about the output above? Note: agew is‘wife’s age’ and ageh is ‘husband’s age’.A. Since the p-value is 0, the true mean agesof husbands and wifes are not equal.B. Since the p-value is 0.173, ‘husband’s age’is a NOT good predictor for ‘wife’s age’.C. Since the p-value is 0.173, ‘husband’s age’is a good predictor for ‘wife’s age’.D. Since the p-value is 0, ‘husband’s age’ is agood predictor for ‘wife’s age’.E. Since the p-value is 0, ‘husband’s age’ is aNOT good predictor for ‘wife’s age’.9. Which of the following best describes what a p-value tells us for the One-way ANOVA F -test?A. The proportion of times we will get a sam-ple slope not equal to 0 when the true slopeis zero.B. The proportion of times we will get samplemeans equal when the true means are notall equal.C. The proportion of times we will get a sam-ple mean not equal to the population mean.D. The proportion of times we will get samplemeans at least this different when the truemeans are all equal.E. The proportion of times we will get a sam-ple slope as different from 0 as we got whenthe true slope is zero.10. Why are the assumptions so important in statis-tical inference, i.e., hypothesis testing?A. They are the only rules we have to go by.B. They are what make the assumed distribu-tions of the data valid.C. They are what minimize the Type I and IIerrors.D. They are what help us decide our conclu-sions.E. They are what help us decide which proce-dure to use.Third world,| Summary of Adult Literacy Ratedeveloping,|OECD| Mean Std. Dev. Freq.------------+------------------------------1-3rdWld | 62.371134 25.803472 972-Devel | 81.666667 21.44317 153-OECD | 94.944444 21.058519 18------------+------------------------------Total | 69.107692 26.59173 130Analysis of VarianceSource SS df MS F Pr > F--------------------------------------------Between 18783.5754 2 9391.788 16.47
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