1. The median is often a better representative of the central value of a data set when the data set: Is bimodal. Has a high standard deviation. Is highly skewed. Has no outliers 2. The data in the Excel spreadsheet linked below provide information on the nutritional content (in grams per serving) of some leading breakfast cereals. For which nutrients is the mean nutrient content per serving greater than the median nutrient content per serving? See attached excel document! Proteins only. Complex carbohydrates only. Both nutrients. Neither nutrient. 3. The histogram below plots the carbon monoxide (CO) emissions (in pounds/minute) of 40 different airplane models at take-off. The distribution is best described as is: Uniform. Heteroskedastic. Normal. Skewed right. 4. The histogram below plots the carbon monoxide (CO) emissions (in pounds/minute) of 40 different airplane models at take-off. Which of the following statements is the best inference that can be drawn from this histogram? The mean amount of carbon monoxide emissions is greater than the median amount of carbon monoxide emissions. The mean amount of carbon monoxide emissions is less than the median amount of carbon monoxide emissions. The mean and median amounts of carbon monoxide emissions are about equal. The relative sizes of the mean and median amounts of carbon monoxide emissions cannot be inferred from the histogram. 5. In the data set shown below, the correlation coefficient of the two variables is: -1.0. -0.5 0.0 None of the above. 6. The data in the Excel spreadsheet linked below give the ages and salaries of the chief executive officers of 59 companies with sales between $5 million and $350 million. The correlation between age and salary can be characterized as: Strong and positive. Strong and negative. Weak and positive. Weak and negative. Age 53 43 33 45 46 55 41 55 36 45 55 50 49 47 69 51 48 Salary ($thousands) 145 621 262 208 362 424 339 736 291 58 498 643 390 332 750 368 659 62 45 37 50 50 50 58 53 57 53 61 47 56 44 46 58 48 38 74 60 32 51 50 40 61 63 56 45 61 70 59 57 69 44 56 50 56 43 48 52 62 48 234 396 300 343 536 543 217 298 1103 406 254 862 204 206 250 21 298 350 800 726 370 536 291 808 543 149 350 242 198 213 296 317 482 155 802 200 282 573 388 250 396 572 7. For a given set of data, the standard deviation measures: The difference between the mean and the data point farthest from the mean. The difference between the mean and the data point nearest to the mean. The difference between the mean and the median. None of the above. 8. The data in the Excel spreadsheet linked below give the average exchange rates of four currencies to the US dollar during October 2002. Over this period, which currency was most volatile relative to the US dollar, as measured by the coefficient of variation? The Brazilian Real. The Euro. The Japanese Yen. The South Korean Won. Date 10/1/2002 10/2/2002 10/3/2002 10/4/2002 10/5/2002 10/6/2002 10/7/2002 10/8/2002 10/9/2002 10/10/2002 10/11/2002 10/12/2002 10/13/2002 10/14/2002 10/15/2002 10/16/2002 10/17/2002 10/18/2002 Brazilian Real per Dollar 3.76 3.62 3.66 3.70 3.78 3.78 3.78 3.76 3.73 3.80 3.96 4.03 4.03 4.03 3.89 3.84 3.92 3.90 Japanese Yen per Dollar 121.70 122.56 122.89 122.70 123.19 123.37 123.21 124.29 124.39 123.28 123.62 124.06 124.05 124.16 124.31 124.70 124.49 125.06 Euro per Dollar 1.01 1.02 1.01 1.01 1.02 1.02 1.02 1.02 1.02 1.01 1.01 1.01 1.01 1.01 1.01 1.02 1.02 1.03 South Korean Won per Dollar 1224.70 1224.50 1230.60 1230.40 1229.40 1229.40 1229.40 1237.70 1254.30 1247.30 1258.20 1257.30 1257.30 1257.30 1259.00 1260.20 1247.20 1249.30 10/19/2002 10/20/2002 10/21/2002 10/22/2002 10/23/2002 10/24/2002 10/25/2002 10/26/2002 10/27/2002 10/28/2002 10/29/2002 10/30/2002 10/31/2002 3.88 3.88 3.88 3.92 3.91 3.92 3.82 3.89 3.89 3.89 3.78 3.83 3.72 125.55 125.56 125.43 124.96 125.16 124.61 124.49 124.34 124.34 124.20 123.62 123.00 122.94 1.03 1.03 1.03 1.03 1.02 1.02 1.02 1.02 1.02 1.02 1.02 1.02 1.02 1241.00 1241.00 1241.00 1237.00 1247.00 1228.90 1228.90 1228.60 1228.60 1228.60 1233.70 1224.40 1234.50 9. A national business magazine intends to survey its subscribers to determine who they think is the "CEO of the Century." Subscribers are invited to complete an online survey. Based only on this information, which of the following can be inferred about the survey results? They will be biased because the magazine's subscribers are unqualified to determine who the CEO of the century is. They will accurately reflect the opinion of the nation as a whole about who the CEO of the century is. They will be unbiased because the respondents will be self-selected. They will be biased because subscribers who have access to the online survey are not representative of the population of subscribers as a whole. 10. A political consultant conducts a survey to determine what position the mayoral candidate she works for should take on a proposed smoking ban in restaurants. Which of the following survey questions will deliver an unbiased response? Source Should the city ban smoking in restaurants to protect our children from second-hand smoke? Should tobacco smoke, a known cause of lung cancer, be banned from public spaces such as restaurants? Does the city have the right to restrict recreational activities, such as moderate consumption of alcohol or tobacco, on the premises of privately-owned businesses? None of the above. 11. In a recently administered IQ test, the scores were distributed normally, with mean 100 and standard deviation 15. What proportion of the test takers scored between 70 and 130? About 68%. About 84%. About 95%. About 99.5%. 12. Which of the following is not true about the Normal Distribution? \\ It is symmetric. Its mean and median are equal. It is completely described by its mean and its standard deviation. It is bimodal. 13. The histogram below shows the underlying distribution pattern of the results of a rolled die. Suppose the die is rolled 50 times and the results are averaged. Suppose this process rolling 50 dice and averaging their results is repeated 100 times. Which of the following best describes the distribution of these 100 averages? Skewed right. Skewed left. Normal. Uniform. 14. A nutrition researcher wants to determine the mean fat content of hen's eggs. She collects a sample of 40 eggs. She calculates a mean fat content of 23 grams, with a sample standard deviation of 8 grams. From these statistics she calculates a 90% confidence interval of [20.9 grams, 25.1 grams]. What can the researcher do to decrease the width of the confidence interval? Increase the confidence level. Decrease the confidence level. Decrease the sample size None of the above. 15. In a random sample of 321 senior citizens, 61 were found to own a home computer. Based on this sample, the 95% confidence interval for the proportion of computer-owners among senior citizens is: [2.6%; 7.4%]. [13.4%; 24.6%]. [14.7%; 23.3%]. The answer cannot be determined from the information given. 16. Preliminary estimates suggest that about 58% of students at a state university favor implementing an honor code. To obtain a 95% confidence interval for the proportion of all students at the university favoring the honor code, what is the minimum sample size needed if the total width of the confidence interval must be less than 5 percentage points (i.e., the confidence interval should extend at most 2.5 percentage points above and below the sample proportion)? 375. 264. 1,498. The answer cannot be determined from the information given. 17. In a survey of twelve Harbor Business School graduates, the mean starting salary was $93,000, with a standard deviation of $17,000. The 95% confidence interval for the average starting salary among all Harbor graduates is: [$83,382; $102,618]. [$82,727; $103,327]. [$82,199; $103,801]. [$59,000; $127,000]. 19. A filling machine in a brewery is designed to fill bottles with 355 ml of hard cider. In practice, however, volumes vary slightly from bottle to bottle. In a sample of 49 bottles, the mean volume of cider is found to be 354 ml, with a standard deviation of 3.5 ml. At a significance level of 0.01, which conclusion can the brewer draw? The true mean volume of all bottles filled is 354 ml. The machine is not filling bottles to an average volume of 355 ml. There is not enough evidence to indicate that the machine is not filling bottles to an average volume of 355 ml. The machine is filling bottles to an average volume of 355 ml. 20. To conduct a one-sided hypothesis test of the claim that houses located on corner lots (corner-lot houses) have higher average selling prices than those located on non-corner lots, the following alternative hypothesis should be used: The average selling price of a corner-lot house is higher than it is commonly believed to be. The average selling price of a corner-lot house is higher than the average selling price of all houses. The average selling price of a corner-lot house is the same as the average selling price of a house not located on a corner lot. The average selling price of a corner-lot house is higher than the average selling price of a house not located on a corner lot. Corner-lot House Price (in $hundreds) 2150 1999 1800 1375 1250 1110 1139 995 900 1695 1553 1300 1020 1020 925 725 1299 1250 1080 1050 835 805 750 773 1295 975 700 2100 600 1844 699 1330 1129 1050 1000 1030 940 Non-corner Lot House Price (in $hundreds) 2050 2080 2150 1900 1560 1450 1449 1270 1235 1170 1180 1155 995 975 975 960 860 1250 922 899 850 876 890 870 700 720 720 749 731 670 2150 1599 1350 1239 1200 1125 1100 874 766 739 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * 1049 955 934 875 889 855 810 799 759 755 750 730 729 710 690 670 619 939 820 780 770 620 540 1070 725 660 580 1580 1160 1109 1050 1045 1020 975 950 920 945 872 870 869 21. The data in the Excel spreadsheet linked above indicate the selling prices of houses located on corner lots ("cornerlot houses") and of houses not located on corner lots. Conduct a one-sided hypothesis test of the claim that corner-lot houses have higher average selling prices than those located on non-corner lots. Using a 99% confidence level, which of the following statements do the data support? Upscale, expensive neighborhoods have more street corners. The average selling price of a corner-lot house is higher than that of the average house not located on a corner lot. The average selling price of a corner-lot house is no more than that of the average house not located on a corner lot. There is not enough evidence to support the claim that the average selling price of a corner-lot house is higher than that of the average house not located on a corner lot. 22. Two semiconductor factories are being compared to see if there is a difference in the average defect rates of the chips they produce. In the first factory, 250 chips are sampled. In the second factory, 350 chips are sampled. The proportions of defective chips are 4.0% and 6.0%, respectively. Using a confidence level of 95%, which of the following statements is supported by the data? There is not sufficient evidence to show a significant difference in the average defect rates of the two factories. There is a significant difference in the average defect rates of the two factories. The first factory's average defect rate is lower than the second factory's on 95 out of 100 days of operation. None of the above. 23. The regression analysis below relates average annual per capita beef consumption (in pounds) and the independent variable "average annual beef price" (in dollars per pound). The coefficient on beef price tells us that: For every price increase of $1, average beef consumption decreases by 9.31 pounds. For every price increase of $1, average beef consumption increases by 9.31 pounds. For every price increase $9.31, average beef consumption decreases by 1 pound. For price increase of $9.31, average beef consumption increases by 1 pound. 24. The regression analysis below relates average annual per capita beef consumption (in pounds) and the independent variable "average annual beef price" (in dollars per pound). In a year in which the average price of beef is at $3.51 per pound, we can expect average annual per capita beef consumption to be approximately: 55.2 pounds 52.6 pounds 53.6 pounds 117.9 pounds 25. The regression analysis below relates average annual per capita beef consumption (in pounds) and the independent variable "average annual per capita pork consumption" (in pounds). At what level is the coefficient of the independent variable pork consumption significant? 0.10. 0.05. 0.01. None of the above. 26. The regression analysis below relates average annual per capita beef consumption (in pounds) and the independent variable "average annual per capita pork consumption" (in pounds). Which of the following statements is true? Beef consumption can never be less than 65.09 pounds. Beef consumption can never be greater than 65.09 pounds. The y-intercept of the regression line is 65.09 pounds. The x-intercept of the regression line is 65.09 pounds. 27. The regression analysis at the bottom relates average annual per capita beef consumption (in pounds) and the independent variables "average annual per capita pork consumption" (in pounds) and "average annual beef price" (in dollars per pound). Which of the independent variables is significant at the 0.01 level? Beef price only. Pork consumption only. Both independent variables. Neither independent variable. 28. The regression analysis at the bottom relates average annual per capita beef consumption (in pounds) and the independent variables "annual per capita pork consumption" (in pounds) and "average annual beef price" (in dollars per pound). The coefficient for beef price, -12, tells us that: For every $1 increase in beef price, average beef consumption decreases by 12 lbs, not controlling for pork consumption. For every $12 drop in beef price, average beef consumption decreases by 1 lbs, not controlling for pork consumption. For every $1 increase in beef price, average beef consumption decreases by 12 lbs, controlling for pork consumption, i.e. holding pork consumption constant. For every $12 decrease in beef price, average beef consumption decreases by 1 lbs, controlling for pork consumption, i.e. holding pork consumption constant. 29. The data in the Excel spreadsheet linked below give the seasonally adjusted value of total new car sales (in millions of dollars) in the United States, total national wage and salary disbursements (referred to here as "compensation") (in billions of dollars), and the employment level in the non-agricultural sector (in thousands) for 44 consecutive quarters. An auto industry executive wants to know how well she can predict new car sales two quarters in advance using the current quarter's compensation data. How many data points can she use in a regression analysis using the data provided? 41. 42. 43. 44. Quarter 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Seasonally Adjusted New Car Sales ($millions) 46,787 44,256 41,523 42,367 43,580 36,392 38,303 40,690 45,653 42,283 44,122 42,022 45,255 45,064 Compensatio n ($billions) 1,193.3 1,217.3 1,254.4 1,284.7 1,319.8 1,335.1 1,360.1 1,411.6 1,451.7 1,478.1 1,512.6 1,530.6 1,542.7 1,563.9 Employment Level (thousands) 87,973 90,021 90,120 91,180 89,832 90,668 89,850 91,276 89,964 91,566 91,405 91,691 89,341 90,310 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 43,560 48,794 51,794 55,270 54,389 60,100 67,741 69,554 65,352 70,472 76,729 79,262 80,554 74,859 79,916 82,091 87,893 86,040 81,814 84,304 85,062 81,125 92,036 92,467 89,461 91,508 95,508 95,871 96,594 88,836 1,579.8 1,586.0 1,610.7 1,643.5 1,671.3 1,715.4 1,755.8 1,793.1 1,819.5 1,847.7 1,882.7 1,939.8 1,976.0 2,012.8 2,044.1 2,069.8 2,097.9 2,128.4 2,163.2 2,211.9 2,265.1 2,325.0 2,358.7 2,405.6 2,452.2 2,505.1 2,560.7 2,572.9 2,586.6 2,612.7 89,324 89,436 88,815 89,920 90,480 92,367 91,637 94,256 95,021 96,547 95,450 97,657 97,985 99,383 98,213 99,850 99,877 101,169 99,922 102,186 102,657 104,522 103,445 106,050 105,963 107,644 106,425 108,741 108,897 110,260 30. The Excel spreadsheet linked below contains the simple regressions of total new car sales (in millions of dollars) on each of two independent variables: "compensation" (in billions of dollars) and "employment level in the nonagricultural sector" (in thousands) . Which of the following independent variables explains more than 90 percent of the observed variation in new car sales? Compensation only. Employment level only. Both independent variables. Neither independent variable. 31. The regression analysis below relates the value of new car sales (in millions of dollars) to compensation (in billions of dollars) and the employment level in the non-agricultural sector (in thousands) for 44 consecutive quarters. Which of the two independent variables is statistically significant at the 0.05 level? Compensation only. Employment level only. Both independent variables. Neither independent variable. 32. The regression analysis below relates the value of new car sales (in millions of dollars) and the independent variables "compensation" (in billions of dollars) and "employment level in the non-agricultural sector" (in thousands) for 44 consecutive quarters. Compare this multiple regression to the simple regressions with compensation and employment level as the respective independent variables. Which of the following is the likely culprit of the dramatic increase in the p-value for employment level in the multiple regression? Multicollinearity. Heteroskedasticity. Nonlinearity. None of the above. 34. A new blood pressure treatment is being tested. The regression analysis below describes the relationship between the 41 test subjects' diastolic blood pressure and the dummy variable "medication." When a test subject is taking the new drug, the value of medication is 1, when not, the value of medication is 0. Which of the following can be inferred from the regression analysis? The medication has no statistically significant effect (at a 0.01 significance level). The use of medication accounts for around 42% of the variation in diastolic blood pressure. On average, test subjects taking the medication report a diastolic blood pressure level about 5 points lower than those not taking the medication. None of the above. Blood Pressure Medication (1 = Yes, 0 = No) 68 72 74 78 78 78 78 78 79 80 80 80 80 80 80 80 80 82 82 82 82 82 82 82 83 84 84 84 86 86 88 88 88 88 88 90 90 90 90 90 92 1 1 1 0 1 1 1 1 1 0 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 1 0 0 1 1 1 0 35. In a regression analysis, a residual plot is: A scatter diagram that plots the values of the residuals against the values of the dependent variable. A scatter diagram that plots the values of the residuals against the values of an independent variable. A histogram that plots the frequency of certain value ranges of the residuals. None of the above. 36. In a regression analysis, if a new independent variable is added and R-squared increases and adjusted R-squared decreases precipitously, what can be concluded? The new independent variable improves the predictive power of the regression model. The new independent variable does not improve the predictive power of the regression model. The regression was performed incorrectly. It is impossible for R-squared to increase and adjusted R-squared decrease simultaneously. The new independent variable's coefficient is not significant at the 0.01 level. 37. The table below displays data the First Bank of Silverhaven (FBS) has collected on the personal savings accounts of its job-holding customers. The table includes data on the distribution of the number of accounts held by Homeowners vs. Non-Homeowners, and by whether the customer is Self-Employed or is Employed by a firm in which he or she does not have an ownership stake. What is the probability that a given account-holder is self-employed? 15% 12% 3% None of the above. 38. The table below displays data the First Bank of Silverhaven (FBS) has collected on the personal savings accounts of its job-holding customers. The table includes data on the distribution of the number of accounts held by Homeowners vs. Non-Homeowners, and by whether the customer is Self-Employed or is Employed by a firm in which he or she does not have an ownership stake. What is the conditional probability that an account-holder is employed by a firm in which he or she does not have an ownership stake, given that the account-holder is a homeowner? 82.9% 68.2% 59.5% None of the above. 39. The table below displays data the First Bank of Silverhaven (FBS) has collected on the personal savings accounts of its job-holding customers. The table includes data on the distribution of the number of accounts held by Homeowners vs. Non-Homeowners, and by whether the customer is Self-Employed or is Employed by a firm in which he or she does not have an ownership stake. Which of the following statements is true? Home ownership and employment status are statistically dependent. The fact that a given personal account is held by a homeowner tells us nothing about the account holder's employment status. The fact that a given personal account is held by a self-employed person tells us nothing about the account-holder's home ownership status. None of the above. 40. Electronics manufacturer SE must decide whether or not to invest in the development of a new type of battery. If the development succeeds, the market for the battery may be large or small. If it doesn't succeed, the development efforts may or may not generate minor innovations that would offset some of the battery's development costs. The tree below summarizes the decision. What is the expected monetary value of developing the new battery? -$0.5 million $0.9 million $1.5 million 41. Electronics manufacturer SE must decide whether or not to invest in the development of a new type of battery. If the development succeeds, the market for the battery may be large or small. If it doesn't succeed, the development efforts may or may not generate minor innovations that would offset some of the battery's development costs. The tree below summarizes the decision. The EMV of developing the new battery is $300,000. Based on EMV, SE should develop the battery. If the manager chooses not to develop the battery, which of the following best describes the manager's attitude towards this decision? Risk averse. Risk neutral. Risk seeking. Cowardly. 42. Electronics manufacturer SE must decide whether or not to invest in the development of a new type of battery. If the development succeeds, the market for the battery may be large or small. If it doesn't succeed, the development efforts may or may not generate minor innovations that would offset some of the battery's development costs. The tree below summarizes the decision. The EMV of developing the new battery is $300,000. Based on EMV, SE should develop the battery. For what values of p = Prob[success] does developing the battery have a lower EMV than not developing the battery? p < 25% p > 25% p < 75% None of the above. 43. Electronics manufacturer SE must decide whether or not to invest in the development of a new type of battery. If the development succeeds, the market for the battery may be large or small. If it doesn't succeed, the development efforts may or may not generate minor innovations that would offset some of the battery's development costs. The tree below summarizes the decision. The EMV of developing the new battery is $300,000. Based on EMV, SE should develop the battery. Given that development is successful, for what endpoint values for a large market does developing the battery have a lower EMV than not developing the battery? Less than $1.2 million. Greater than $1.2 million. Greater than $0.75 million. None of the above. 44. The manager of the Eris Shoe Company must decide whether or not to contract a controversial sports celebrity as its spokesperson. The new spokesperson's value to Eris depends heavily on consumers' perception of him. An initial decision analysis based on available data reveals that the expected monetary value of contracting the new spokesperson is $260,000. For $50,000 Eris can engage a market research firm that will help Eris learn more about how consumers might react to the celebrity. The EMV of buying this sample information (assuming it is free) for this decision is $300,000. The tree below summarizes Eris's decision. Based on EMV analysis, Eris's manager should: Hire the research firm. Not hire the research firm, but contract the new spokesperson. Not hire the research firm and not contract the new spokesperson. The answer cannot be determined from the information provided. Cereal 100% Bran All-Bran Almond Delight Apple Cinnamon Cheerios Apple Jacks Bran Chex Bran Flakes Cap'n'Crunch Cheerios Cinnamon Toast Crunch Cocoa Puffs Corn Chex Corn Flakes Corn Pops Count Chocula Cracklin' Oat Bran Cream of Wheat (Quick) Crispix Double Chex Froot Loops Frosted Flakes Frosted Mini-Wheats Fruit & Fibre Dates, Walnuts, and Oats Fruity Pebbles Golden Grahams Grape Nuts Flakes Grape-Nuts Great Grains Pecan Honey Nut Cheerios Honey-comb Kix Life Lucky Charms Maypo Muesli Raisins, Dates, & Almonds Muesli Raisins, Peaches, & Pecans Mueslix Crispy Blend Nut&Honey Crunch Nutri-grain Wheat Post Nat. Raisin Bran Product 19 Puffed Rice Puffed Wheat Quaker Oat Squares Raisin Bran Raisin Nut Bran Raisin Squares Rice Chex Rice Krispies Shredded Wheat Smacks Special K Total Corn Flakes Total Raisin Bran Total Whole Grain Triples Trix Wheat Chex Wheaties serving)Prot ein (grams per serving) 4 4 2 2 2 2 3 1 6 1 1 2 2 1 1 3 3 2 2 2 1 3 3 1 1 3 3 3 3 1 2 4 2 4 4 4 3 2 3 3 3 1 2 4 3 3 2 1 2 2 2 6 2 3 3 2 1 3 3 (grams per serving)Complex Carbohydrates (grams per serving) 5 7 14 11 11 15 13 12 17 13 12 22 21 13 12 10 21 21 18 11 14 14 12 13 15 15 17 13 12 14 21 12 12 16 16 16 17 15 18 11 20 13 10 14 14 11 15 23 22 16 9 16 21 15 16 21 13 17 17 qattachments_b508b9fa8e3f8a6846336f80fb4531e4498280ba.xlsx Cereals 07/22/2015