Question

Call: formula -MoiveS8ookSales MoiveS8oxOfficeReceipts+ Moi veSProductionCosts+ MoiveSPronotionalCosts) Residuals Min 1Q Median 3 Max 4.883-2.511 -1.528 1.560 6.721 Coefficients: Estimate Std. Error t value Pr(>ltl) 0.9996 4.7607 0.210 0.841 (Intercept) MoiveS8oxOfficeReceipts 0.3487 .2218 1.536 0.175 MoiveSProductionCosts -0.7565 1.1564 -0.654 0.537 MoiveSPromotionalCosts 2.7566 1.9605 -1.486 8.209 Residual standard error: 4.836 on 6 degrees of freedon Multiple R-squared: 0.4175, Adjusted R-squared: 0.1263 F-statistic: 1.434 on 3 and 6 DF. p-value: 8.3229 13. Given alpha 0.05, based on the output, which of the following variables is significantly contribute to the model's predictive power: a. Book Office Receipt b. Production Costs c. Promotional Costs d. None of the above 14. After taking into consideration both the additional information each new independent variable brings to the regression model and the changed degrees of freedom, the total variances of dependent variable explained by this regression model is: 12.63% a. b. 41.75% 34.07% С. d. 22.18% 15. Given alpha 0.05, we are trying to test if this regression model is significantly providing more predictive power than average y model (the lazy model). What are the hypothesis testing decision and conclusion: a. we reject the null hypothesis and our model is no better than the lazy model; b. we fail to reject the null hypothesis and our model is significantly better than lazy morel; we reject the null hypothesis and our model is significantly better than lazy model; d. we fail to reject the null hypothesis and our model is no better than the lazy model; c. 16. Giving the following observed frequency table of income level from 100 randomly selected sample, and the expected distribution from the population, in order to test if the observed frequency is significantly different from the expected distribution which of the R command can we use for this test:

Answer 1

13. For none of the variables, p value < 0.05

So,

None of the variables are significant.

Option D is correct.

14. Variation explained = Adjusted R-sq = 12.63%

Option A is correct.

15. Option D is correct.