The Kramer Corporation's marketing manager calculates a regression, where the quantity demanded of the firm's product (designated as "C1") is the dependent variable and the price of the product (designated as "C2") and consumers' disposable income (designated as "C3") are in de pen dent variables. The Minitab printout for this regression follows:
MTB > regress c1 on 2 predictors in c2 and c3
The regression equation is
C1 = 40.8 - 1.02 C2 + 0.00667 C3

s = 1.361 R-sq = 91.62% R-sq(adj) = 90.8%
Analysis of Variance

SOURCE DF SEQ SS
C2 1 420.25
C3 1 2.67
a. What is the intercept of the regression?
b. What is the estimated regression coefficient of the product's price?
c. What is the estimated regression coefficient of disposable income?
d. What is the multiple coefficient of determination?
e. What is the standard error of estimate?
f. What is the probability that the observed value of the F statistic could arise by chance, given that neither of the in de pen dent variables has any effect on the dependent variable?
g. What is the probability, if the true value of the regression coefficient of price is zero, that the t statistic is as large (in absolute terms) as we observe?
h. What is the probability, if the true value of the regression coefficient of disposable income is zero, that the t statistic is as large (in absolute terms) as we observe?
i. Describe briefly what this regression means.

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Predictor constant C2 СЗ Coef 40.833 Stdev t-ratio 1.112 36.74 0.000 -1.02500 0.06807 15.06 0.000 1.20 0.244 0.006667 0.005558 SOURCE Regression Error Total DF MS 2 422.92 211.46 114.11 0.000 21 38.92 23 461.83 1.85