The analyst in Exercise 28 realized the data were in need of transformation because of the nonlinearity between the variables. Economists commonly take the logarithm

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The analyst in Exercise 28 realized the data were in need of transformation because of the nonlinearity between the variables. Economists commonly take the logarithm of these variables to make the relation-ship more nearly linear, and she did too. (These are base 10 logs.) The dependent variable is LogSales. The conditions for regression inference now appear to be satisfied.

a) Is there a significant linear association between LogAssets and LogSales? Find the t- value and P-value to test an appropriate hypothesis and state your conclusion in context.
b) Do you think that a company€™s assets serve as a useful predictor of their sales?

Dependent variable is: LogSales R-squared 33.9% s=0.4278 with 79-2-77 degrees of freedom Variable Coefficient SE(Coeff) t-Ratio P-Value Intercept 1.303 0.321 4.06 0.0001 LogAssets 0.578 0.0919 6.28