| 1. | The impact of a single drink on blood alcohol content (BAC, in percent of volume) depends on gender and stature. For a woman weighing 120 pounds, the BAC increases by 0.038 for each drink taken in one hour. One drink is defined as a serving of 12 oz of beer or 4 oz of table wine. What is the equation of the regression line for predicting BAC from number of drinks for a 120-pound woman? a) y = 120 + 0.038x. b)y = 12 + 0.038x or y = 4 + 0.038x, depending on what she drank. c)y = 0.038x. The BAC limit in the United States is 0.08 for drivers over 21 years old. What BAC would we expect for a 120-pound woman having 2 drinks in one hour? Give your answer to 3 decimal places. Fill in the blank: Would her BAC be over the legal limit, assuming she is over 21 years old? Would it be safe driving? a)The predicted BAC is under the limit and therefore it would be perfectly safe for her to drive. b)The predicted BAC is over the limit and therefore it wouldn't be safe for her to drive. c)The predicted BAC is just under the limit. However, the prediction represents what we can expect on average and the actual measured BAC could be lower or higher than the predicted BAC. | | 3. | There is a positive relationship between the wealth of nations (measured in dollars of income per capita adjusted for purchasing power) and the life expectancy at birth (measured in years) in these nations. In part, this association reflects causation - wealth enables health through better nutrition and increased access to medical infrastructures. Suggest other explanations for the association between the wealth and health of nations. (Ask yourself how people's health can influence the economy.) Choose one or more plausible explanations: a)Nations with serious and persisting social crises (such as conicts or a civil war) provide poor living conditions, high early mortality, and a devastated economy. b)People who live longer spend more money throughout life leading to a weaker economy. c)Nations with widespread health care problems cannot support a strong economy. d)Healthier people are less productive and therefore contribute less to the economy. | 4. | Figure 4.8 is a scatterplot of tree frog mating call frequency (in notes per second) against outside temperature (in Celsius) for 16 American bird-voiced tree frogs. picture number 1 The line is the least-squares regression line for predicting call frequency from temperature. If another frog of this species initiates a mating call when the outside temperature is 24 degrees Celsius, you predict the call frequency (in notes/s) to be close to a)5 b)7 c)9 | 5. | Figure 4.8 is a scatterplot of tree frog mating call frequency (in notes per second) against outside temperature (in Celsius) for 16 American bird-voiced tree frogs. |
picture number 2 The line is the least-squares regression line for predicting call frequency from temperature. In this data, temperature explains about 75% of the variability in call frequency. The correlation between call frequency and temperature is close to |
| 6. | Step 1: For a class project, you measure the weight in grams and the tail length in millimeters (mm) of a group of mice. The equation of the least-squares line for predicting tail length from weight is predicted tail length = 20 + 3 weight.If you had measured the tail length in centimeters instead of millimeters, what would be the slope of the regression line? (There are 10 millimeters in a centimeter) | | | | | c)3/10 = 0.3 For a class project, you measure the weight in grams and the tail length in millimeters (mm) of a group of mice. The equation of the least-squares line for predicting tail length from weight is predicted tail length = 22 + 4 weight.If you had measured the tail length in centimeters instead of millimeters, what would be the slope of the regression line? (There are 10 millimeters in a centimeter) | | | | | c)4/10 = 0.4 For a class project, you measure the weight in grams and the tail length in millimeters (mm) of a group of mice. The equation of the least-squares line for predicting tail length from weight is predicted tail length = 23 + 5 weight.If you had measured the tail length in centimeters instead of millimeters, what would be the slope of the regression line? (There are 10 millimeters in a centimeter) | | | | | c)5/10 = 0.5 For a class project, you measure the weight in grams and the tail length in millimeters (mm) of a group of mice. The equation of the least-squares line for predicting tail length from weight is predicted tail length = 20 + 6 weight.If you had measured the tail length in centimeters instead of millimeters, what would be the slope of the regression line? (There are 10 millimeters in a centimeter) | | | | | 6 For a class project, you measure the weight in grams and the tail length in millimeters (mm) of a group of mice. The equation of the least-squares line for predicting tail length from weight is predicted tail length = 22 + 3 weight.If you had measured the tail length in centimeters instead of millimeters, what would be the slope of the regression line? (There are 10 millimeters in a centimeter) | | | | | 3/10 = 0.3 For a class project, you measure the weight in grams and the tail length in millimeters (mm) of a group of mice. The equation of the least-squares line for predicting tail length from weight is predicted tail length = 23 + 4 weight.If you had measured the tail length in centimeters instead of millimeters, what would be the slope of the regression line? (There are 10 millimeters in a centimeter) | | | | | 4 For a class project, you measure the weight in grams and the tail length in millimeters (mm) of a group of mice. The equation of the least-squares line for predicting tail length from weight is predicted tail length = 20 + 5 weight.If you had measured the tail length in centimeters instead of millimeters, what would be the slope of the regression line? (There are 10 millimeters in a centimeter) |
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