Q14. Using data from the past 20 quarters, Brent calculates the t-statistic for marketing expenditures to be 3.68 and the t-statistic for salespeople at 2.19. At a 5% significance level, the two-tailed critical values are tc = +/- 2.127. This most likely indicates that: A) the t-statistic has 18 degrees of freedom. B) both independent variables are statistically significant. C) the null hypothesis should not be rejected.
Q15. Brent calculated that the sum of squared errors (SSE) for the variables is 267. The mean squared error (MSE) would be: A) 14.831. B) 14.055. C) 15.706.
Q16. Brent is trying to explain the concept of the standard error of estimate (SEE) to Johnson. In his explanation, Brent makes three points about the SEE: - Point 1: The SEE is the standard deviation of the differences between the estimated values for the independent variables and the actual observations for the independent variable.
- Point 2: Any violation of the basic assumptions of a multiple regression model is going to affect the SEE.
- Point 3: If there is a strong relationship between the variables and the SSE is small, the individual estimation errors will also be small.
How many of Brent’s points are most accurate? A) 1 of Brent’s points are correct. B) All 3 of Brent’s points are correct. C) 2 of Brent’s points are correct.
Q17. Assuming that next year’s marketing expenditures are $3,500,000 and there are five salespeople, predicted sales for Mega Flowers will be: A) $11,600,000. B) $24,200,000. C) $2,400,000.
Q18. Brent would like to further investigate whether at least one of the independent variables can explain a significant portion of the variation of the dependent variable. Which of the following methods would be best for Brent to use? A) The F-statistic. B) The multiple coefficient of determination. C) An ANOVA table.
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发表于 2009-1-8 11:53
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