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Question
A microcomputer manufacturer has developed a regression model relating his sales (yin $10,000s) with three independent variables. The three independent variables are price per unit (Price in $100s), advertising (Adver in $1,000s) and the number of product lines (Lines). Part of the regression results is shown below.| ANOVA | ||||
| df | SS | MS | F | |
| Regression | 2708.61 | |||
| Error | 14 | 2840.51 | ||
| Coefficients | Standard Error | |||
| Intercept | 1.0211 | 22.8752 | ||
| Price | -0.1524 | 0.1411 | ||
| Adver | 0.8849 | 0.2886 | ||
| Lines | -0.1463 | 1.5340 |
a. Use the above results and write the regression equation that can be used to predict sales.
b. If the manufacturer has 10 product lines, advertising of $40,000, and the price per unit is $3,000, what is your estimate of their sales? Give your answer in dollars.
c. Compute the coefficient of determination and fully interpret its meaning.
d. At
= 0.05, test to see if there is a significant relationship between sales and unit price.e. At
= 0.05, test to see if there is a significant relationship between sales and the number of product lines.f. Is the regression model significant? (Perform an Ftest.)
g. Fully interpret the meaning of the regression (coefficient of price) per unit that is, the slope for the price per unit.
h. What has been the sample size for this analysis?
Answer
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