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# Regression analysis

See attached data file.

Terry and Associated is a specialized medical testing center in Denver, Colorado. One of the firm's major sources of revenue is a kit used to test for elevated amounts of lead in the blood. Workers in auto body shops, those in the lawn care industry, and commercial house painters are exposed to large amounts of lead and thus must be randomly tested. It is expensive to conduct the test, so the kits are delivered on demand to a variety of locations throughout the Denver area.

Kathleen Terry, the owner, is concerned about setting appropriate costs for each delivery. To investigate, Ms. Terry gathered information on a random sample of 50 recent deliveries. Factors thought to be related to the cost of delivering the kit were:

Prep: The time in minutes between when the customized order is phoned into the company and when it is ready for delivery.
Delivery: The actual travel time in minutes from Terry's plant to the customer.
Mileage: The distance in miles from Terry's plant to the customer.

1. Develop a multiple linear regression equation that describes the relationship between the cost of delivery and the other variables. Do these three variables explain a reasonable amount of the variation in the dependent variable? Estimate the delivery cost for a kit that takes 10 minutes for preparation, takes 30 minutes to deliver, and must cover a distance of 14 miles.

2. Test to determine that at least one net regression coefficient differs from zero. Also test to see whether any of the variables can be dropped from the analysis. If some of the variables can be dropped, rerun the regression equation until only significant variables are included.

3. Write a brief report interpreting the final regression equation.

#### Solution Summary

The solution provides step by step method for the calculation of regression model . Formula for the calculation and Interpretations of the results are also included.

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