Q1. Which of the following is most commonly used to predict the value of a dependent variable based on one independent variable in regression analysis?
A. Simple linear regression
B. Multiple linear regression
C. Logistic regression
D. Polynomial regression
Q2. In regression analysis, what does the slope of the regression line represent?
A. The average value of the dependent variable
B. The rate of change of the dependent variable with respect to the independent variable
C. The intercept of the regression line
D. The total error in prediction
Q3. Which of the following indicates how well the regression model fits the data?
A. Standard deviation
B. R-squared value
C. Mean
D. Correlation coefficient
Q4. When the residuals in regression analysis show a clear pattern, what does this imply?
A. The regression model may be misspecified
B. The dependent variable is constant
C. The independent variable is insignificant
D. The regression line is perfect
Q5. If two independent variables in multiple regression are highly correlated, what problem may arise?
A. Multicollinearity
B. Homoscedasticity
C. Autocorrelation
D. Heteroscedasticity
Q6. Which regression technique would you use if the relationship between the variables is not linear but follows a curve?
A. Polynomial regression
B. Simple linear regression
C. Logistic regression
D. Stepwise regression
Q7. A researcher wants to predict whether patients recover or not (yes/no) based on age and treatment type. Which regression should be used?
A. Logistic regression
B. Simple linear regression
C. Polynomial regression
D. Stepwise regression
Q8. Which of the following would most likely violate the assumptions of linear regression?
A. Non-constant variance of residuals (heteroscedasticity)
B. Independent residuals
C. Normally distributed residuals
D. Linearity between variables
Q9. If you add more independent variables to a regression model, what typically happens to the R-squared value?
A. It usually increases or stays the same
B. It always decreases
C. It always stays the same
D. It becomes zero
Q10. A business wants to predict sales based on advertising spend, price, and season. What type of regression analysis should they use?
A. Multiple linear regression
B. Simple linear regression
C. Logistic regression
D. Ridge regression
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