The printout shows the results of a first-order regression analysis relating the sales price y of a product to the time in hours x1 and the cost of raw materials x2 needed to make the product.
SUMMARY OUTPUT
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.9975783020.9951624680.9903249361.1852507235
ANOVA
Regression Residual Total df224 SS 577.99036142.809638554580.8 MS 288.99521.404819 F 205.717 Significance F0.004837532
Intercept Time Materials Coefficients −26.48433735−2.1686746998.142168675 Standard Error 3.6746687734.114065321.094681583 t Stat −7.20727−0.527147.437933 P-value 0.0187130.6507320.0176 Lower 95% −42.29517198−19.87008143.432130693 Upper 95% −10.6735027115.53273212.0512.85220666
a. What is the least squares prediction equation?
b. Identify the SSE from the printout.
c. Find the estimator of σ2 for the model.
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