CWID 38. The following regression equation was obtained using the five independe
ID: 1161407 • Letter: C
Question
CWID 38. The following regression equation was obtained using the five independent variables. sales 19.7 0.00063 outlets 1.74 cars0.410 income 2.04 age - The regression equation is 0.034 bosses Predictor Constant outlets cars Coef SE Coef 5.422 0.000629 0.002638 0.5530 0.40994 0.04385 0.8779 0.1880 -19.672 1.7399 2.0357 -3.63 0.022 -0.24 0.823 0.035 9.35 0.001 2.32 0.081 0.18 0.864 ncome age bosses -0.0344 S1.507 R- Sqaz 99.4% R-Sq(adj) -98.7% Analysis of Variance Source DF MS 318.76 2.27 0.000 1593.81 9.08 1602.89 Regression 140.36 Residual BrTOr 4 Total Minitab Software) Answer Question a) What is sample size? /0 b) Write the estimated regression equation -1.7-.000 3X,t c) What's the sample regression coefficients of bo d) What's the sample regression coefficients of b2 e) What's the value of the estimated variance of the 9.4 o is expanel by de equatian regression What's the value of the standard error of the regression g) What's the value of the estimated variance of the b2 What's the value of the standard error of the b2 alw i) Is the result significant when using F statistic to test the significant of the relationship at a 0.05 level of significance Rejet null, et luston 15 P ageExplanation / Answer
Except the below ones, rest all look good:
b. Write the estimated regression equation in this form:
Predicted Sales = -19.7 - 0.00063*Outlets + 1.74*cars + 0.410*income + 2.04*age - 0.034*bosses
(also note that you copied the coefficient of X5 incorrectly.its -0.034.
e. The estimated variance of regression is mentioned in the ANOVA table. It is 1593.81.
g. estimated variance of b2 = 0.5530^2 = 0.3058.
The SE coefficient gives us the standard error of each estimated parameters. The square of the SE coefficient is the variance of b2.
h. 0.5530 - see column 3 (SE coef) The SE coefficient gives us the standard error of each estimated parameters.
i. The p-value is 0.00 < 0.05. It means we can reject the null hypothesis that all of the slope parameters are equal to 0. That is, we do not reject the Alternate hypothesis - at least one of the coefficients is non-zero.