A manager uses regression to express sales as a function of advertising expenditures (X1), and per capita income (X2) in your sales area. The following multiple linear regression equation is developed:
Y = 10 + .51X1 + .45X2
The coefficient of determination is .96
This coefficient of determination explains that:
A) 96% of sales variations are explained by the equation
B) The dependent variable is not related to advertising expenditures and per capita income
C) 96% of sales variations are due to an error term
D) Only 4% of the sales variations are explained by advertising expenditures and per capita income
96% of sales variations are explained by the equation |
The coefficient of determination determines the variance in future sales |
Option A is correct |
A manager uses regression to express sales as a function of advertising expenditures (X1), and pe...
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures y = 35+12r16x2 where =inventory investment ($1000s) 1 x2 = advertising expenditures ($1000s) sales ($1000s) a. Predict the sales resulting from a $15,000 investment in inventory and an advertising budget of $10,000. $ b. Interpret bi and b2 in this estimated regression equation. bi Sales can be expected to-Select your answer by $12 for every dollar increase in Select your answer is held...
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