Multiple Regression and Correlation Analysis. John Wood, a financial analyst for a major automobile cor¬ poration, has been monitoring the funds used in adver¬ tising campaigns and the funds used for automobile factory rebates. Financial data have been accumulated for the last 24 months along with customer sales, that is, automobiles sold. Wood contends that there may be a relationship between the level of automobile sales and funds expended on advertising and/or factory rebates. If such a relationship can be determined, the company may be able to estimate sales demand based on various levels of funding commitments for one or both types of expenditures.

Regression equations and supporting statistical val¬ ues developed for the various relationships between variables are as follows:

Coefficient of Determination Equation r2 Equation 1 D = 2.455 + .188A .4140 Equation 2 D = 2.491 + .44R .3140 Equation 3 R = 6.052 + .005A .0002 Equation 4 D = -.184 + .186A + .437R .7030 Standard Error of the Estimate s 1.325 1.434 2.202

.922 where the notations used in the equations are as follows:

A = advertising funds in $100,000 R = funds for factory rebates in $1,000,000 D = customer sales demand (automobiles sold) in 10,000 units The appropriate t values for use in determining con¬ fidence intervals are as follows:

50% confidence.69 95% confidence.2.07 Required:

(1)Assuming the corporation is projecting advertising expenditures amounting to $1,500,000 and factory rebate expenditures amounting to $12,000,000 for the next time period, calculate expected customer demand in units using:

(a) Equation 1

(b) Equation 2

(2) Assume that equation 4 is employed to estimate a total customer demand of 104,160 automobiles for a time period. Using a 50% confidence level, deter¬ mine the range of automobile sales that could occur during the time period.

(3) Select the regression equation that would be most advantageous to predict customer sales demand and explain why it is the best.

(4) Explain the significance of equation 3 and how it may be used in evaluating equation 4.