Regression Analysis MCQs
Regression Analysis MCQs
Try to answer these 20+ Regression Analysis MCQs and check your understanding of the Regression Analysis subject.
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1: A bivariate regression contains more than one independent variable.
A. True
B. False
2: The slope coefficient in regression is represented by b.
A. True
B. False
3: The regression formula gives us only empirical values.
A. True
B. False
4: Hypothesis testing using multiple regression is typically considered a two-tailed test.
A. True
B. False
5: Slope coefficients with larger standard errors are generally less accurate than ones with smaller standard errors.
A. True
B. False
6: Which of the following statements provides the best definition for ordinary least squares regression.
A. A regression analysis that uses one IV and one DV
B. A regression analysis that uses two or more IVs and one DV
C. A common procedure for estimating regression equations
D. None of these
7: The regression equation produces which type of values?
A. Predicted y’s
B. Empirical y’s
C. X's
D. Predicted y’s and empirical y’s
8: What is the most accurate definition for line of best fit?
A. A random line drawn anywhere
B. A line that comes closer to the data points than any other lines
C. A line that touches all of the data points
D. A linear equation
9: What item(s) must be calculated before creating a regression equation?
A. The intercept
B. The slope coefficient
C. The intercept and the slope coefficient
D. The standardized beta
10: What does the correlation of prediction address?
A. The empirical y values
B. The IV
C. The DV
D. The quality of predictions
11: What is the primary reason bivariate regression is problematic?
A. Social factors typically have more than one cause.
B. It involves too much math.
C. Because it is too similar to correlation.
D. None of these
12: Which of the following statements provides a definition for the intercept in regression analysis?
A. The point in which the line crosses the X-axis
B. The point in which the line crosses the Y-axis
C. Where two lines bisect each other
D. Where the normal curve crosses a line
13: What is the null hypothesis in a regression analysis?
A. No relationship exists between all the IVs.
B. There is no difference between groups.
C. There is no relationship between IVs and DVs.
D. Regression equations have different nulls depending on circumstance.
14: The slope in a regression equation is defined as what?
A. How the IV changes in an equation
B. Rise over run
C. The normal distribution
D. A measure of the change in the DV produced by a one-unit change in the IV
15: What must be found FIRST in order to determine if a b value is statistically significant?
A. The standard deviation
B. The standard error
C. The t score
D. The mean
16: _____ is a standardized slope coefficient that ranges from –1.00 to +1.00 and can be interpreted similarly to a correlation so that the magnitude of an independent variable–dependent variable relationship can be assessed.
A. None of these
B. The z distribution
C. The mean
D. Beta weight
17: _____ is defined as a regression analysis that uses one independent variable and one dependent variable.
A. All values in the distribution are distributed normally.
B. Two-thirds of the scores in the distribution lie one standard deviation above or below the mean.
C. Bivariate regression
D. All of these
18: _____ is known as a dichotomous independent variable.
A. All of these
B. A policy analysis
C. The same as an empirical outcome
D. Dummy variable
19: Is intercept the point at which the regression line crosses the y-axis; also the value of y when x = 0?
A. True
B. False
20: _____ is a regression analysis that uses two or more independent variables and one dependent variable.
A. The alternative hypothesis is true.
B. All of these
C. Either can be true depending on the circumstances.
D. Multiple regression
21: _____ is defined as a slope coefficient that measures the individual impact of an independent variable on a dependent variable while holding other independent variables constant.
A. Rise over run
B. A measure of the change in the DV produced by a one-unit change in the IV
C. Partial slope coefficient
D. All of these
22: _____ is known as a technique for modeling linear relationships between one or more independent variables and one dependent variable wherein each independent variable is evaluated on the basis of its ability to accurately predict the values of the dependent variable.
A. Regression analysis
B. None of these
C. The slope coefficient
D. The intercept
23: Is residual the difference between a predicted value and an empirical value on a dependent variable?
A. True
B. False
24: _____ is the steepness of the regression line and a measure of the change in the dependent variable produced by a one-unit increase in an independent variable.
A. Slope
B. They are part of Step 2 in hypothesis testing.
C. They are not part of hypothesis testing.
D. All of these
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Regression Analysis MCQs
