MCQs Regression Analysis Quiz 7

The post is about the MCQs Regression Analysis Quiz with Answers. There are 20 multiple-choice questions from correlation analysis, regression analysis, correlation matrix, coefficient of determination, residuals, predicted values, Model selection, regularization techniques, etc. Let us start with the MCQs regression analysis quiz.

Online Multiple Choice Questions about Correlation and Regression Analysis

1. Which statements accurately describe coefficients and p-values for regression model interpretation?

 
 
 
 

2. Which of the following statements accurately describes a randomized, controlled experiment?

 
 
 
 

3. What is the sum of the squared differences between each observed value and the associated predicted value?

 
 
 
 

4. Adjusted R squared is a variation of the R squared regression evaluation metric that ————— unnecessary explanatory variables.

 
 
 
 

5. What type of visualization uses a series of scatterplots that show the relationships between pairs of variables?

 
 
 
 

6. The best-fit line is the line that fits the data best by minimizing some —————.

 
 
 
 

7. What variable selection process begins with the full model that has all possible independent variables?

 
 
 
 

8. What does the circumflex symbol, or “hat” (^), indicate when used over a coefficient?

 
 
 
 

9. R squared measures the —————- in the dependent variable $Y$, which is explained by the independent variable, $X$.

 
 
 
 

10. Which linear regression evaluation metric is sensitive to large errors?

 
 
 
 

11. Regression analysis aims to use math to define the ————– between the sample $X$’s and $Y$’s to understand how the variables interact.

 
 
 
 

12. Which of the following statements accurately describes the normality assumption?

 
 
 
 

13. What term describes an inverse relationship between two variables?

 
 
 
 

14. What is the difference between observed or actual values and the predicted values of a regression line?

 
 
 
 

15. Regression models are groups of ————– techniques that use data to estimate the relationships between a single dependent variable and one or more independent variables.

 
 
 
 

16. ————- is a technique that estimates the relationship between a continuous dependent variable and one or more independent variables.

 
 
 
 

17. ————- finds the mean of $Y$ given a particular value of $X$.

 
 
 
 

18. Which of the following are regularized regression techniques?

 
 
 
 

19. How does a data professional determine if a linearity assumption is met?

 
 
 
 

20. What concept refers to how two independent variables affect the $Y$ dependent variable?

 
 
 
 

MCQs Regression Analysis Quiz with Answers

MCQs Regression Analysis Quiz with Answers

  • What term describes an inverse relationship between two variables?
  • Regression analysis aims to use math to define the ————– between the sample $X$’s and $Y$’s to understand how the variables interact.
  • Regression models are groups of ————– techniques that use data to estimate the relationships between a single dependent variable and one or more independent variables.
  • ————- finds the mean of $Y$ given a particular value of $X$.
  • ————- is a technique that estimates the relationship between a continuous dependent variable and one or more independent variables.
  • The best-fit line is the line that fits the data best by minimizing some —————.
  • What is the sum of the squared differences between each observed value and the associated predicted value?
  • What does the circumflex symbol, or “hat” (^), indicate when used over a coefficient?
  • How does a data professional determine if a linearity assumption is met?
  • Which of the following statements accurately describes the normality assumption?
  • What type of visualization uses a series of scatterplots that show the relationships between pairs of variables?
  • R squared measures the —————- in the dependent variable $Y$, which is explained by the independent variable, $X$.
  • Which linear regression evaluation metric is sensitive to large errors?
  • Which statements accurately describe coefficients and p-values for regression model interpretation?
  • What is the difference between observed or actual values and the predicted values of a regression line?
  • Which of the following statements accurately describes a randomized, controlled experiment?
  • What concept refers to how two independent variables affect the $Y$ dependent variable?
  • Adjusted R squared is a variation of the R squared regression evaluation metric that ————— unnecessary explanatory variables.
  • What variable selection process begins with the full model that has all possible independent variables?
  • Which of the following are regularized regression techniques?
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