# Multiple Choice Quizzes

Take the quiz test your understanding of the key concepts covered in the chapter. Try testing yourself before you read the chapter to see where your strengths and weaknesses are, then test yourself again once you’ve read the chapter to see how well you’ve understood.

1. What does a dummy-variable regression analysis examine?

1. The relationship between one continuous dependent and one continuous independent variable
2. The relationship between one categorical dependent and one continuous independent variable
3. The relationship between one continuous dependent and one categorical independent variable
4. The relationship between one continuous dependent and one dichotomous variable

c. The relationship between one continuous dependent and one categorical independent variable

d. The relationship between one continuous dependent and one dichotomous variable

2. Which of the following is incorrect?

1. Regression with one dummy variable (predictor) corresponds directly to an independent analysis of variance (ANOVA)
2. Regression with more than one dummy variable including a covariate corresponds directly to an independent analysis of covariance (ANCOVA)
3. Regression with more than one dummy variable (predictor) corresponds directly to an independent analysis of variance (ANOVA)
4. Regression with one dummy variable (predictor) corresponds directly to an independent t-test

a. Regression with one dummy variable (predictor) corresponds directly to an independent analysis of variance (ANOVA)

3. Which of the following procedures can be used to compare the means of the included groups in a dummy-variable regression model?

1. Changing the reference group
2. Linear combination
3. Standardization
4. Not possible

a. Changing the reference group

b. Linear combination

4. Why is the number of dummy variables to be entered into the regression model always equal to the number of groups (g) minus 1 (g-1)?

1. To avoid the model misspecification
2. To increase the R-squared value
3. To avoid the situation of perfect multicollinearity
4. To control for other variables in the model

c. To avoid the situation of perfect multicollinearity

5. How do we interpret a dummy variable coefficient?

1. The difference between two means
2. The difference between two coefficients
3. The difference between two R-square values
4. None of the above