MCQs Correlation and Regression Quiz 8

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The post is about the MCQs Correlation and Regression Quiz. There are 20 multiple-choice questions about correlation and regression analysis, covering MCQs about correlation analysis, regression analysis assumptions, coefficient of determination, predicted and predictor variables, etc. Let us start with the MCQS correlation and Regression Quiz.

Online Multiple Choice Questions about Correlation and Regression Analysis with Answers

1. The major difference between regression analysis and correlation analysis is that in regression analysis:

 
 
 
 

2. The output of a certain chemical-processing machine is linearly related to temperature. At $-10^\circ C$ the processor output is 200 KGs per hour at $40^\circ C$ the output is 220 KGs per hour. Calculate the linear equation for KGs per hour of output ($Y$) as a function of temperature in degrees Celsius ($X$):

 
 
 
 

3. Given that $X=1.50 + 0.50Y$, what is the predicted value for a $Y$ value of 6?

 
 
 
 

4. What information is given by a value of the coefficient of determination?

 
 
 
 

5. The coefficient of partial determination differs from the coefficient of multiple determinations in that

 
 
 
 

6. The distribution of sample correlation is

 
 
 
 

7. If one wished to test the relationship between social and juvenile delinquency with the number of siblings held constant, the most appropriate technique would be

 
 
 
 

8. In regression equation $y=\alpha + \beta x + \varepsilon$, both $x$ and $y$ variables are

 
 
 
 

9. Which of the following is NOT an assumption underlying regression analysis?

 
 
 
 

10. The term homoscedasticity refers to

 
 
 
 

11. The estimated coefficient of determination is equal to all except which of the following?

 
 
 
 

12. The regression model can be used to

 
 
 
 

13. Two variables are said to be uncorrelated if

 
 
 
 

14. The dependent variable is also known as

 
 
 
 

15. Whenever predictions are made from the estimated regression line, the relation between $X$ and $Y$ is assumed to be:

 
 
 
 

16. The regression coefficients may have the wrong sign for the following reasons:

 
 
 
 

17. A random sample of paired observations has been selected and the sample correlation coefficient is -1. From this result, we know that:

 
 
 
 

18. Which of the following regression equations represents the strongest relationship between $X$ and $Y$?

 
 
 
 

19. The sum of squares of which type of deviations is minimized by the least square regression:

 
 
 
 

20. The coefficient of multiple determination is 0.81. Thus, the multiple correlation coefficient is

 
 
 
 

Online MCQs Correlation and Regression Quiz

  • The distribution of sample correlation is
  • The major difference between regression analysis and correlation analysis is that in regression analysis:
  • The term homoscedasticity refers to
  • The sum of squares of which type of deviations is minimized by the least square regression:
  • A random sample of paired observations has been selected and the sample correlation coefficient is -1. From this result, we know that:
  • The output of a certain chemical-processing machine is linearly related to temperature. At $-10^\circ C$ the processor output is 200 KGs per hour at $40^\circ C$ the output is 220 KGs per hour. Calculate the linear equation for KGs per hour of output ($Y$) as a function of temperature in degrees Celsius ($X$):
  • What information is given by a value of the coefficient of determination?
  • Whenever predictions are made from the estimated regression line, the relation between $X$ and $Y$ is assumed to be:
  • The estimated coefficient of determination is equal to all except which of the following?
  • The coefficient of partial determination differs from the coefficient of multiple determinations in that
  • The coefficient of multiple determination is 0.81. Thus, the multiple correlation coefficient is
  • In regression equation $y=\alpha + \beta x + \varepsilon$, both $x$ and $y$ variables are
  • The dependent variable is also known as
  • The regression coefficients may have the wrong sign for the following reasons:
  • The regression model can be used to
  • If one wished to test the relationship between social and juvenile delinquency with the number of siblings held constant, the most appropriate technique would be
  • Given that $X=1.50 + 0.50Y$, what is the predicted value for a $Y$ value of 6?
  • Which of the following regression equations represents the strongest relationship between $X$ and $Y$?
  • Which of the following is NOT an assumption underlying regression analysis?
  • Two variables are said to be uncorrelated if
mcqs correlation and regression quiz

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