13. the standard error of the estimate (se) is essentially the ____.

A) mean of the residuals
B) standard deviation of the residuals
C) mean of the independent variable
D) standard deviation of the independent variable
6.

A multiple regression analysis including 50 data points and 5 independent variables results in Σ e_i² = 40. The multiple standard error of estimate will be ____.

A) 0.901
B) 0.888
C) 0.800
D) 0.953
E) 0.894
7.

In linear regression, a dummy variable is used ____.

A) to represent residual variables
B) to represent missing data in each sample
C) to include hypothetical data in the regression equation
D) to include categorical variables in the regression equation
E) when “dumb” responses are included in the data
8. In linear regression, we can have an interaction variable. Algebraically, the interaction variable is the ____ with another variable in the regression equation.A) sum
B) ratio
C) product
D) mean
9. A two-tailed test is one where ____.A) results in only one direction can lead to rejection of the null hypothesis
B) negative sample means lead to rejection of the null hypothesis
C) results in either of two directions can lead to rejection of the null hypothesis
D) no results lead to the rejection of the null hypothesis
10.

Which of the following is not one of the assumptions of regression?

A) There is a population regression line.
B) The error term is normally distributed.
C) The standard deviation of the dependent variable increases as the independent variables increase.
D) The errors are probabilistically independent.
11.

In the standardized value (b_i – β_i) / s_bi, the symbol s_bi represents the ____.

A) mean of b_i
B) variance of b_i
C) standard error of b_i
D) degrees of freedom of b_i
12.

The value k in the number of degrees of freedom, n-k-1, for the sampling distribution of the regression coefficients represents ____.

A) the sample size
B) the population size
C) the number of coefficients in the regression equation, including the constant
D) the number of independent variables included in the equation
13. The ANOVA table splits the total variation into two parts. They are the ____.A) acceptable and unacceptable variation
B) adequate and inadequate variation
C) resolved and unresolved variation
D) explained and unexplained variation
14. The null and alternative hypotheses divide all possibilities into ____.A) two sets that overlap
B) two non-overlapping sets
C) two sets that may or may not overlap
D) as many sets as necessary to cover all possibilities
15. One-tailed alternatives are phrased in terms of ____.A) ≠
B) < or >
C) =
D) ≤ or ≥ 
16. A type II error occurs when ____.A) the null hypothesis is incorrectly accepted when it is false
B) the null hypothesis is incorrectly rejected when it is true
C) the sample mean differs from the population mean
D) the test is biased
17. In statistical analysis, the burden of proof lies traditionally with the ____.A) alternative hypothesis
B) null hypothesis
C) analyst
D) facts presented to the statistical analyst
18. Smaller p-values indicate more evidence in support of the ____.A) null hypothesis
B) alternative hypothesis
C) quality of the researcher
D) none of these options
19. A type I error occurs when the ____.A) null hypothesis is incorrectly accepted when it is false
B) null hypothesis is incorrectly rejected when it is true
C) sample mean differs from the population mean
D) test is biased
20. The power of a test is the probability that we ____.A) reject the null hypothesis when the alternative hypothesis is false
B) reject the null hypothesis when the alternative hypothesis is true
C) accept the null hypothesis when the alternative hypothesis is false
D) accept the null hypothesis when the alternative hypothesis is true