1. Which one of the following statements is true?

a. When predicting one quantitative variable based on another, the variable you are trying to predict should always go on the x-axis of the scatterplot.

b. The intercept in a regression equation can never negative.

c. The correlation coefficient has no units.

d. A very strong relationship between variables can result in a value of r that is larger than 1.

e. A correlation coefficient can only range in value from 0 to 1.

2. A weather forecaster examines the weather patterns in a random sample of cities in order to better understand how the number of days of rain a city gets per year is related to the number of hours of sunshine that city gets per year.The regression equation to predict hours of sunshine based on days of rain is as follows:

Predicted hours of sunshine = 2847 - 6.88(days of rain).

From this regression equation, we know that r, or the correlation between days of rain and hours of sunshine, must be

a. weak.

b. strong.

c. positive.

d. negative.

e. non-linear.

3. Data is collected on the distance of several hikes (in miles), along with the amount of time (in minutes) the hike is expected to take. All hikes in the data set are between 0.5 miles and 10 miles long, and the relationship between distance and time is linear and strong. The regression equation to predict time based on distance is as follows: Predicted time = -1.266 + 31.48 (distance). Suppose we want to use the regression equation to predict the time it takes to complete a particular hike. For which one of the following distances would using the regression equation result in extrapolation?

a. 1 mile

b. 4.5 miles

c. 6.8 miles

d. 9 miles

e. None of the above distances would result in extrapolation.

4. If you look at many cities in the United States, there is a positive correlation between the number of Target stores in the city and the number of Walmart stores in the city. This means that

a. for every one Target store in a city, there is exactly one Walmart store.

b. the employees who work at Target also work at Walmart.

c. as the number of Walmart stores in a city increases by one, the number of Target stores also increases by exactly one.

d. in order for a city to be productive, there must be at least one Target store and at least one Walmart store in that city.

e. as the number of Walmart stores goes up in a city, the number of Target stores also tends to go up.

5. Is there a relationship between the amount of protein (in grams) and the number of calories in items sold at fast-food restaurants? The scatterplot below shows the results of an analysis of 126 fast food items. For each item, the protein and calorie contents were measured. To predict number of calories based on protein content, the following regression equation was constructed: Predicted number of calories = 199.6 + 13.4 (grams of protein). Which one of the following statements is a correct interpretation of this equation?