1. For a random sample of 30 countries, the linear correlation coefficient between the infant mortality rate and the average number of cars per capita was found to be r = -0.717. What does this imply? Does this suggest that if people buy more cars, this could lower the infant mortality rate? Why or why not? What is a likely lurking variable?

1. A manager wishes to determine the relationship between the number of miles traveled (in hundreds of miles) by her sales representatives and their amount of sales (in thousands of dollars) per month in an attempt to predict future sales.He has collected the following data.

Would it be appropriate to use this data to predict the sales of someone who drove 900 miles? Why or why not?

Miles Sales

2 31

3 33

10 78

7 62

8 65

15 61

3 48

1 55

11 120

1. A manager wishes to determine the relationship between the number of miles traveled (in hundreds of miles) by her sales representatives and their amount of sales (in thousands of dollars) per month in an attempt to predict future sales.

Here is a part of the Excel regression output for the data.What is the equation for the line based on this output?

Coefficients Standard Error t Stat P-value

Intercept 37.91575092 13.15092845 2.8831235 0.023546

miles 3.529304029 1.635370567 2.1581066 0.067797