Data on pollution and cost of medical care for elderly people were given in Exercise 5.14 and are also shown here. The accompanying data are a measure of pollution (micrograms of particulate matter per cubic meter of air) and the cost of medical care per person over age 65 for six geographic regions of the United States.

The equation of the least-squares regression line for this data set is y^ 5 1082.2 2 4.691x, where y medical cost and x pollution.

a. Compute the six residuals.

b. What is the value of the correlation coef fi cient for this data set? Does the value of r indicate that the linear relationship between pollution and medical cost is strong, moderate, or weak? Explain.

c. Construct a residual plot. Are there any unusual features of the plot?

d. The observation for the West, (40.0, 899), has an x value that is far removed from the other x values in the sample. Is this observation influential in determining the values of the slope and/or intercept of the least-squares line? Justify your answer.

Transcribed Image Text:

Region Pollution Cost of Medical Care North 30.0 915 Upper South 31.8 891 Deep South 32.1 968 West South 26.8 972 Big Sky 30.4 952 West 40.0 899