Consider the soft drink delivery time data in Example 3.1.

Example 3.1

a. Find the simple correlation between cases \(\left(x_{1}\right)\) an distance \(\left(x_{2}\right)\).
b. Find the variance inflation factors.
c. Find the condition number of \(\mathbf{X}^{\prime} \mathbf{X}\). Is there evidence of multicollinearity in these data?

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A soft drink bottler is analyzing the vending machine service routes in his distribu- tion system. He is interested in predicting the amount of time required by the route driver to service the vending machines in an outlet. This service activity includes stocking the machine with beverage products and minor maintenance or housekeep- ing. The industrial engineer responsible for the study has suggested that the two most important variables affecting the delivery time (y) are the number of cases of product stocked (x) and the distance walked by the route driver (x2). The engineer has collected 25 observations on delivery time, which are shown in Table 3.2. (Note that this is an expansion of the data set used in Example 2.9.) We will fit the multiple linear regression model y=Bo+B1x1 +2x2 + to the delivery time data in Table 3.2.