Sample Final Mat 117 Prof. Kazlow All questions are worth 3 points each. You may use a scientific, graphing or statistical calculator. You may not use a cell phone, pda, or computer on this exam. When doing computations using your calculator, report all digits your calculator can compute. When copying results from computer output, report all digits contains in the output. Trailing zeroes do not have to be reported. You have one hour and 50 minutes to complete your exam. Questions 1-3: The following output are MegaStat analyses of score on a class' exam. Descriptive statistics #1 20 49.90 21.36 count mean sample standard deviation sample variance minimum maximum range 84 68 Frequency Distribution - Quantitative Data lower upper midpoint width 18 frequency 3 cumulative percent frequency percent 15.0 3 15.0 10 < 25 25 < 40 40 < 55 48 3 15.0 55 < 70 63 5 25.0 15 70 < 85 77 5 25.0 20 20 100.0 20.0 7 35.0 50.0 100.0 1. What is the minimum data value? 2. What is the class midpoint of the class [25, 40) 3. What is the relative cumulative frequency of the class [55, 70) 4. The following is a list of five of the world's busiest airports by passenger traffic for 2010. Name Hartsfield-Jackson Capital International London Heathrow O'Hare Tokyo Location Atlanta, Georgia, United States Beijing, China London, United Kingdom Chicago, Illinois, United States Tokyo, Japan # of Passengers (in millions) 89 74 67 66 64 True or False: This data can be best represented by a histogram? Page 1 of 6 Mat 117 Sample Final Prof. Kazlow 5. Suppose that, on average, electricians earn approximately = 54 000 dollars per year in the United States. Assume that the distribution for electrician's yearly earnings is normally distributed and that the standard deviation is = 12 000 dollars.What is the probability that the average salary of four randomly selected electricians exceeds $60,000? 6. The snowfall (in inches) during the month of January in a particular geographic region is normally distributed with a standard deviation of 16.75. In the last 12 years, the sample average of snowfall is computed as 122.50. Construct a 90% confidence interval of the average snowfall in this region. 7. A professional sports organization is going to implement a test for steroids. The test gives a positive reaction in 94% of the people who have taken the steroid. However, it erroneously gives a positive reaction in 4% of the people who have not taken the steroid. What is the probability of a Type I and Type II error using the null hypothesis \"the individual has not taken steroids.\" A. Type I: 4%, Type II: 6% C. Type I: 94%, Type II: 4% B. Type I: 6%, Type II: 4% D. Type I: 4%, Type II: 94% 8. A fast-food franchise is considering building a restaurant at a busy intersection. A financial advisor determines that the site is acceptable only if, on average, more than 300 automobiles pass the location per hour. The advisor tests the following hypotheses: Ho: 300 vs. Ha: 300 . The consequences of committing a Type I error would be that _______________. A. The franchiser builds on an acceptable site B. The franchiser builds on an unacceptable site C. The franchiser does not build on an acceptable site D. The franchiser does not build on an unacceptable site 9. Many cities around the United States are installing LED streetlights, in part to combat crime by improving visibility after dusk. An urban police department claims that the proportion of crimes committed after dusk will fall below the current level of 0.84 if LED streetlights are installed. Specify the null and alternative hypotheses to test the police department's claim. A. Ho: p = 0.84 vs. Ha: p 0.84 B. Ho: p 0.84 vs. Ha: p 0.84 C. Ho: p 0.84 vs. Ha: p 0.84 D. Ho: p 0.84 vs. Ha: p 0.84 Questions 10-13: In August of 2010, Massachusetts enacted a 150-day right-to-cure period that mandates that lenders give homeowners who fall behind on their mortgage an extra five months to become current before beginning foreclosure proceedings. Policymakers claimed that the policy would result in a higher proportion of delinquent borrowers becoming current on their mortgages. To test this claim, researchers took a sample of 244 homeowners in danger of foreclosure in the time period surrounding the enactment of this law. Of the 100 who fell behind just before the law was enacted, 30 were able to avoid foreclosure, and of 144 who fell behind just after the law was enacted, 48 were able to avoid foreclosure. Let p B and p A represent the proportion of delinquent borrowers who avoid foreclosure just before and just after the right-to-cure law is enacted, respectively. Page 2 of 6 Sample Final Mat 117 Prof. Kazlow 10. State the null and alternative hypothesis will test the policymakers' claim. 11. What test statistic should be used to test the hypothesis? Give the formula. Questions 12 & 13: Below is a partial MegaStat output base upon the data. Hypothesis test for two independent proportions p1 0.3 30/100 30. 100 p2 0.3333 pc 0.3197 p (as decimal) 48/144 78/244 p (as fraction) 48. 78. X 144 244 n -0.0333 difference 0. hypothesized difference 0.0607 std. error -0.55 z 12. What is the p-value of the test? 13. Should you accept or reject the null hypothesis based upon a 5% level of significance? Explain. Questions 14-16: A new sales training program has been instituted at a rent-to-own company. Prior to the training, 10 employees were tested on their knowledge of products offered by the company. Once the training was completed, the employees were tested again in an effort to determine whether the training program was effective. Scores are known to be normally distributed. The sample scores on the tests are listed next. Pre-test Score Post-test Score 66 75 94 100 87 93 84 85 76 75 88 90 14. What are the appropriate hypotheses to determine if the training increases scores? 15. What test statistic should be used to test the hypotheses? Give its formula? 16. What degree of freedom does the test statistic have? Page 3 of 6 Sample Final Mat 117 Prof. Kazlow Questions 17-20: A farmer uses a lot of fertilizer to grow his crops. The farmer's manager thinks fertilizer products from distributor A contain more of the nitrogen that his plants need than distributor B's fertilizer does. He takes two independent samples of four batches of fertilizer from each distributor and measures the amount of nitrogen in each batch. Fertilizer from distributor A contained 23 pounds per batch and fertilizer from distributor B contained 18 pounds per batch. Suppose the population standard deviation for distributor A and distributor B is four pounds per batch and five pounds per batch, respectively. Assume the distribution of nitrogen in fertilizer is normally distributed. Let A and B represent the average amount of nitrogen per batch for fertilizer's A and B, respectively. 17. What null and alternative hypotheses should the farmer use? 18. What test statistic should the farmer use to test the above hypotheses? Give its formula. 19. What critical value should the farmer use to test the above hypotheses at the 10% level of significance? 20. Assuming the test statistic has a value of 1.5617, should the null hypothesis be accepted or rejected at the 10% level of significance? 21. Suppose you want to perform a test to compare the mean GPA of all freshmen with the mean GPA of all sophomores in a college? What type of sampling is required for this test? A. B. C. D. Independent sampling with qualitative data Independent sampling with quantitative data Matched-pairs sampling with qualitative data Matched-pairs sampling with quantitative data 22. True or False: The null hypothesis Ho: 2 10 is rejected at the 5% level of significance if 2 the value of the test statistic exceeds 0.025 . 23. For a sample of 10 observations drawn from a normally distributed population, we obtain the sample mean and the sample variance as 50 and 75, respectively. We want to determine whether the population variance is greater than 70. The critical value at a 5% significance level is: A. 16.919 B. 9.642 C. 3.325 D. 1.645 E. None of these. 24. The chi-square test of a contingency table is a test of independence for: A. A single qualitative variable C. Two quantitative variables B. Two qualitative variables D. Three or more quantitative variables 25. The chi-square test of a contingency table is valid when the expected cell frequencies are: A. Equal to 0 C. At least 5 B. More than 0 but less than 5 D. Negative Page 4 of 6 Sample Final Mat 117 Prof. Kazlow 26. True or False: Another name for an explanatory variable is the dependent variable. Questions -: The following table shows the cross-classification of a random sample of companies' accounting practices (either straight line, declining balance, or both) and country (either France, Germany, or UK). Accounting Practice Straight line Country Observed Expected (O - E)_ / E Declining Balance Observed Expected (O - E)_ / E Both Observed Expected (O - E)_ / E Total Observed Expected (O - E)_ / E France Germany UK Total 20 19.038 0.049 14 11 19.427 3.655 16 30 22.535 2.473 15 16.624 15 23 49 49.000 0.102 50 50.000 6.661 13 18.841 1.811 58 58.000 4.442 61 61.000 6.177 45 45.000 0.353 51 51.000 4.675 157 157.000 11.205 11.205chi-square df .0244p-value 27. What would be the appropriate null and alternative hypotheses for the test above? 28. What are the expected number of companies from Germany that use a Declining Balance Accounting Method? 29. What is the cell chi-square for UK companies that use Declining Balances. 30. What is the degree of freedom for the test statistic? 31. Should accept or reject the null hypothesis at the 5% level of significance? 32. Explain that the meaning of the answer above in everyday English. Page 5 of 6 Sample Final Mat 117 Prof. Kazlow 33. Look at the scatterplot of the values of two random variables. Describe their linear relationship? A. No relationship. C. Strong and positive. E. Weak and negative. B. Strong and negative. D. Weak and positive. Questions 34-36: Attached is a MegaStat printout. The analysis tries to forecast the value of a home (in thousands of dollars) from the number of bathrooms in the home: Regression Analysis r2 0.385 r 0.620 Std. Error of Estimate26.086 Regression output variables Intercept Bathrooms a= b= coefficients 254.473 44.454 n24 k1 Dep. Var.Value std. error t (df=22) 11.982 3.710 confidence interval p-value 95% lower 95% upper .0012 19.605 69.303 34. What is the equation of the regression line? 35. What is the predicted value of a home with two bathrooms? Express your answer in dollars. 36. Do you think that more bathrooms increase the value of a home? Please explain. (6 points) Page 6 of 6