Question

1) Data was gathered from several professional golfers in order to determine if there is a relationship between average driving distance (in yards) and accuracy (in percentage). This data is presented in the scatterplot below. Suppose we go on to compute the correlation coefficient, r. In this example, the units of r would be what?

A. There are no units

B. Yards

C. Percentage

D. Yards per percentage

E. Percentage per yard

70 65 60 Accuracy (%) 55 50 45 285 290 295 310 315 320 300 305 Distance (yards)

2. In a study of academic achievement within elementary school classrooms, researchers noticed a correlation between class size (or number of students in the classroom) and average achievement test score for the class. The correlation was r = – 0.79. From this information, we can conclude that

A. an arithmetic error was made because a correlation should always be greater than 0. B. average achievement test score tends to be higher in smaller classes.

C. average achievement test score tends to be lower in smaller classes.

D. average achievement test score is not associated at all with class size.

E. 79% of elementary school students in large classes will perform poorly on achievement tests.

3. Is average attendance at a baseball game higher if the team wins more of its games? During one baseball season, data was gathered from many major league teams who had won between 60 and 100 games. From each team, the number of wins during the season was recorded, along with the average game attendance. The relationship between the variables was linear and strong.

The following regression equation was put together to predict average attendance based on number of wins:

Predicted average attendance = –14364.5 + 538.9 (number of wins).

Based on this regression equation, we’d predict the average attendance to be about _____________ for a team that wins 85 games.

A. 31,442

B. 60,171

C. 45,807

D. 14,903

E. 14,365

4. Several items from the menu at Starbucks were analyzed in order to determine calorie and carbohydrate content. Is there a relationship between the number of calories in a menu item and the number of grams of carbohydrates in that menu item? When a scatterplot was constructed, the relationship was observed to be linear. The regression equation to predict carbohydrate content based on calorie content was as follows: Predicted grams of carbohydrates = 8.94 + 0.11(number of calories). What does the slope in this regression equation tell us?

A. The correlation between number of calories and grams of carbohydrates is obviously weak.

B. A menu item with 8.94 grams of carbohydrates will only have 0.11 calories.

C. As number of calories goes up by 1, we predict grams of carbohydrates to increase

by 8.94.

D. As number of calories goes up by 1, we predict grams of carbohydrates to increase

by 0.11.

E. 11% of the variability in grams of carbohydrates can be explained by the regression

equation.

Answer 1

0 The unit of the correlation coefficient (6) Ans? AD These are no units, 2) Correlation r=-0.79 (negative association relationship) Ansi c. Average achievement test score tends to be lower in smalles classes, 3) The regression equation is Predicted average allendence -14364.5+538-9 (number of wine) predict the average attendence to be about -14364.5+538.9%85531442 Based on this regression equation, weld for team that wing 85 games, 4) What the slope in this regression equation tell us that Ans? D) As wees As number of calories we predict grams of carbohydrates to increase by ato, gows up by I 0.11,