[TA03-012] By looking at the insurance rates on the table in Applied Example 3.6, we can see that as a person ages, the insurance rate increases.

You probably anticipated that, but let’s take a closer look at one of specific situations listed.

a. Calculate the correlation coefficient, r, for the variables issue age (x) and monthly rate for

$250,000 for males.

b. Draw a scatter diagram of the insurance data for males at the $250,000 based on age (x).

c. Do the data appear to have a linear pattern?

Explain.

d. Explain how a nonlinear data pattern can have a high linear correlation coefficient.

e. Explain why you should have anticipated this nonlinear pattern.

f. (Optional) Investigate one or more of the other five columns of insurance rates answering parts a through e for each.