Chapter 4CHAPTER 4The stock market did well during the 1990s. Here are the percent total returns (change in price plus dividends paid) for the Standard & Poor's 500 stock index:The next three questions are related to this situation.1. The correlation of U.S. stock returns with overseas stock returns during these years was r = 0.44. This tells you that(a) when U.S. stocks rose, overseas stocks also tended to rise, but the connection was not very strong(b) when U.S. stocks rose, overseas stocks rose by almost exactly the same amount(c) when U.S. stocks rose, overseas stocks tended to fall, but the connection was not very strong(d) there is almost no relationship between changes in U.S. stocks and changes in overseas stocks(e) nothing, because this is not a possible value of r2. If x is the return on U.S. stocks and y is the return on overseas stocks in the same year, the least-squares regression line for predicting y from x is y = -2.7 + 0.47x. You think U.S. stocks will have a return of 10% in 1999. Using this regression line, you predict that the return on overseas stocks will be(a) 7.4% (b) -2.23% (c) 2% (d) 3.17% (e) 27%3. Stock returns are measured in percent. What are the units of the mean, the median, the quartiles, the standard deviation, and the correlation between U.S. and overseas returns?(a) all are measured in percent.(b) all are measured in percent except the standard deviation, which is measured in squared percent.(c) all are measured in percent except the correlation, which is a number that has no units.(d) all are measured in percent except the correlation, which is measured in squared percent.(e) the mean, median, and quartiles are in percents, the standard deviation is in squared percent, and the correlation has no units.4. Consider a large number of countries around the world. There is a positive correlation betweenthe number of Nintendo games per person x and the average life expectancy y. Does this mean that we could increase the life expectancy in Rwanda by shipping Nintendo games to that country?(a) Yes: the correlation says that as Nintendos go up, so does life expectancy.(b) No: if the correlation were negative we could accept that conclusion, but this correlation is positive.(c) Yes: positive correlation means that if we increase x, then y will also increase.(d) No: the positive correlation just shows that richer countries have both more Nintendos and higher life expectancies.(e) It makes no sense to calculate correlation between these variables.53Chapter 45. Suppose that the correlation between the scores of students on Exam 1 and Exam 2 in a statistics class is r = 0.7. One way to interpret r is to say what percent of the variation in Exam 2 scores can be explained by the straight line relationship between Exam 2 scores and Exam 1 scores. This percent is about(a) 84% (b) 70% (c) 49% (d) 30% (e) 16%6. A study of grades at a large university finds that the mean GPA for all undergraduates is 2.77. The distribution of grades is roughly normal. To make this description useful we must also know(a) the correlation (b) the median(c) the slope (d) the standard deviation(e) the regression equation7. “Least-squares” in the term “least-squares regression line” refers to(a) Minimizing the sum of the squares of all values of the explanatory variable.(b) Minimizing the sum of the squares of all values of the response variable.(c) Minimizing products of each value of the response variable and the predicted value based on the regression equation.(d) Minimizing the sum of the squares of the residuals.(e) Minimizing the squares of the differences between each value of the response variable and each value of the explanatory variable.8. Which statistical measure is not strongly affected by a few outliers in the data?(a) the mean(b) the median(c) the standard deviation(d) the correlation coefficient(e) the slope of the least-squares regression line9. A "regression line" is not just any line drawn through the points of a scatterplot. What is special about a regression line?(a) It passes through all the points.(b) It always uses the least-squares idea.(c) It has slope equal to the correlation between the two variables.(d) It describes how a response variable y changes as an explanatory variable x takes different values.(e) Half the points are always above the line and half are below the line.54Chapter 4How well does the number of beers a person drinks predict his or her blood alcohol content? Sixteen student volunteers at Ohio State University drank a randomly assigned number of cans ofbeer. Thirty minutes later, a police officer measured their blood alcohol content (BAC). A scatterplot of the data appears below. The next six questions concern this relationship.10. One person drank 9 beers. You see from the scatterplot that his BAC was about(a) 19 (b) 9 (c) 5 (d) 0.19 (e) 0.0511. The scatterplot shows(a) a weak negative relationship(b) a moderately strong negative relationship(c) almost no relationship(d) a weak positive relationship(e) a moderately strong positive relationship 12. A plausible value of the correlation between number of beers and blood alcohol content, based on the scatterplot, is(a) r = -0.9 (b) r = -0.3 (c) r close to 0 (d) r = 0.3 (e) r = 0.955Chapter 413. The least-squares regression line for predicting blood alcohol content from number of beers is y = -0.013 + 0.018x. The slope 0.018 of this line tells us that(a) the correlation between number of beers and BAC is 0.018(b) on average, BAC increases by 0.018 for each additional beer a person drinks(c) the ratio of beer-over-BAC is 0.018.(d) a person who drinks no beer will still have a BAC of 0.018(e) the average BAC of all the individuals in the study was 0.01814. The least-squares regression line for predicting blood alcohol content from number of beers is y = -0.013 + 0.018x. Using this line, you predict that the BAC of a person who drinks 5 beers will be about(a) 0.025 (b) 0.077 (c) 0.09 (d) 0.103 (e) 0.88715. Based the least squares regression line from the previous problem, what is the residual for the person who drank two beers and had a BAC of 0.03?(a) –0.019 (b) –0.007 (c) 0.007 (d) 0.019 (e) 0.04916. The United Nations has data on the percent of adult males and females who are illiterate in each of these 142 countries. The correlation between male illiteracy rate and female illiteracy rate is r = 0.945. This tells us that(a) countries with high male