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Multiple Regression Analysis

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A shoe manufacturer is considering the development of a new brand of running shoes. The business problem facing the marketing analyst is to determine which variables should be used to predict durability (i.e. the effect of long term impact). Two independent variables under consideration are X1 (FOREIMP), a measurement of the forefoot shock absorbing capability, and X2 (MIDSOLE), a measurement of the change in impact properties over time. The dependent variable Y is LTIMP, a measure of the shoe's durability after a repeated impact test. Data are collected from a random sample of 15 types of currently manufactured running shoes, with the following results:

Variable Coefficients Standard Error t statistic p-Value
INTERCEPT -0.02686 0.06905 -0.39 0.7034
FOREIMP 0.79116 0.06295 12.57 0.0
MIDSOLE 0.60484 0.07174 8.43 0.0

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This solution explains the output of a multiple regression analysis.

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The multiple regression equation is
= -0.02686 + 0.79116 X1 + 0.60484 X2
In the multiple regression model, the coefficient of X1 ...

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