ATI TEAS EXAM REVIEW
1. In a regression analysis, the error term 3 is a random variable with a mean or
expected value of
a. zero
b. one
c. any positiv... [Show More] e value
d. any value - A
2. The coefficient of determination
a. cannot be negative
b. is the square root of the coefficient of correlation
c. is the same as the coefficient of correlation
d. can be negative or positive - A
3. If the coefficient of determination is a positive value, then the coefficient of correlation
a. must also be positive
b. must be zero
c. can be either negative or positive
d. must be larger than 1 - C
4. In regression analysis, the model in the form is called
a. regression equation
b. correlation equation
c. estimated regression equation
d. regression model - D
5. The mathematical equation relating the independent variable to the expected value of
the dependent variable; that is, E(y) = 0 + 1x, is known as
a. regression equation
b. correlation equation
c. estimated regression equation
d. regression model - A
6. The model developed from sample data that has the form of is known as
a. regression equation
b. correlation equation
c. estimated regression equation
d. regression model - C
7. In the following estimated regression equation
a. b1 is the slope
b. b1 is the intercept
c. b0 is the slope
d. None of these alternatives is correct. - A
8. In regression analysis, the unbiased estimate of the variance is
a. coefficient of correlation
b. coefficient of determination
c. mean square error
d. slope of the regression equation - C
9. The interval estimate of the mean value of y for a given value of x is
a. prediction interval estimate
b. confidence interval estimate
c. average regression
d. x versus y correlation interval - B
10. The interval estimate of an *individual value* of y for a given value of x is
a. prediction interval estimate
b. confidence interval estimate
c. average regression
d. x versus y correlation interval - A
11. The standard error is the
a. t-statistic squared
b. square root of SSE
c. square root of SST
d. square root of MSE - D
12. If only MSE is known, you can compute the
a. r square
b. coefficient of determination
c. standard error
d. all of these alternatives are correct - C
13. The value of the coefficient of correlation (R)
a. can be equal to the value of the coefficient of determination (R2)
b. can never be equal to the value of the coefficient of determination (R2)
c. is always smaller than the value of the coefficient of determination
d. is always larger than the value of the coefficient of determination - A
14. In a regression analysis the standard error is determined to be 4. In this situation the
MSE
a. is 2
b. is 16
c. depends on the sample size
d. depends on the degrees of freedom - B
15. In regression analysis, which of the following is not a required assumption about the
error term?
a. The expected value of the error term is one.
b. The variance of the error term is the same for all values of X.
c. The values of the error term are independent.
d. The error term is normally distributed. - A
16. A regression analysis between sales (Y in $1000) and advertising (X in dollars)
resulted in the following equation
= 30,000 + 4 X
The above equation implies that an
a. increase of $4 in advertising is associated with an increase of $4,000 in sales
b. increase of $1 in advertising is associated with an increase of $4 in sales
c. increase of $1 in advertising is associated with an increase of $34,000 in sales
d. increase of $1 in advertising is associated with an increase of $4,000 in sales - D
17. Regression analysis is a statistical procedure for developing a mathematical
equation that describes how
a. one independent and one or more dependent variables are related
b. several independent and several dependent variables are related
c. one dependent and one or more independent variables are related
d. None of these alternatives is correct. - C
18. In a simple regression analysis (where Y is a dependent and X an independent
variable), if the Y intercept is positive, then
a. there is a positive correlation between X and Y
b. if X is increased, Y must also increase
c. if Y is increased, X must also increase
d. None of these alternatives is correct. - D
19. In regression analysis, the variable that is being predicted is the
a. dependent variable
b. independent variable
c. intervening variable
d. is usually x - A
20. The equation that describes how the dependent variable (y) is related to the
independent variable (x) is called
a. the correlation model
b. the regression model
c. correlation analysis
d. None of these alternatives is correct. - B
21. In regression analysis, the independent variable is
a. used to predict other independent variables
b. used to predict the dependent variable
c. called the intervening variable
d. the variable that is being predicted - B
22. Larger values of r2 imply that the observations are more closely grouped about the
a. average value of the independent variables
b. average value of the dependent variable
c. least squares line
d. Origin - C
23. In a regression analysis, the coefficient of determination is 0.4225. The coefficient of
correlation in this situation is
a. 0.65
b. 0.1785
c. any positive value
d. any value - A
24. In a regression analysis, the coefficient of correlation is 0.16. The coefficient of
determination in this situation is
a. 0.4000
b. 0.0256
c. 4
d. 2.56 - B
25. In simple linear regression analysis, which of the following is not true?
a. The F test and the t test yield the same conclusion.
b. The F test and the t test may or may not yield the same conclusion.
c. The relationship between X and Y is represented by means of a straight line.
d. The value of F = t2. - B
26. Correlation analysis is used to determine
a. the equation of the regression line
b. the strength of the relationship between the dependent and the independent variables
c. a specific value of the dependent variable for a given value of the independent
variable
d. None of these alternatives is correct. - B
27. In a regression and correlation analysis if r2 = 1, then
a. SSE must also be equal to one
b. SSE must be equal to zero
c. SSE can be any positive value
d. SSE must be negative - B
28. In a regression and correlation analysis if r2 = 1, then
a. SSE = SST
b. SSE = 1
c. SSR = SSE
d. SSR = SST - D
29. In a regression analysis, t [Show Less]
