Correlation and Regression 1

This quiz is about MCQ on correlation and regression analysis.

This Section contains MCQs on Correlation Analysis, Simple Regression Analysis, Multiple Regression Analysis, Coefficient of Determination (Explained Variation), Unexplained Variation, Model Selection Criteria, Model Assumptions, Interpretation of results, Intercept, Slope, Partial Correlation, Significance tests, OLS Assumptions, Multicollinearity, Heteroscedasticity, Autocorrelation, etc. Let us start MCQ on Correlation and Regression Analysis

1. If regression line $\hat{y}=5$ then value of regression coefficient of $y$ on $x$ is

 
 
 
 

2. If each of $X$ variable is divided by 5 and $Y$ by 10 then $\beta_{YX}$ by coded value is:

 
 
 
 

3. The regression coefficient is independent of

 
 
 
 

4. The average of two regression coefficients is always greater than or equal to the correction coefficient is called:

 
 
 
 

5. If the two lines of regression are perpendicular to each other, the correlation coefficient $r=$ is:

 
 
 
 

6. If $\rho$ is the correlation coefficient, the quantity $\sqrt{1-\rho^2}$ is termed as

 
 
 
 

7. If $\rho=0$, the lines of regression are:

 
 
 
 

8. The range of a partial correlation coefficient is:

 
 
 
 

9. In multiple linear regression analysis, the square root of Mean Squared Error (MSE) is called the:

 
 
 
 

10. Homogeneity of three or more population correlation coefficients can be tested by

 
 
 
 

11. If all the actual and estimated values of $Y$ are the same on the regression line, the sum of squares of errors will be

 
 
 
 

12. If the correlation coefficient between the variables $X$ and $Y$ is $\rho$, the correlation coefficient between $X^2$ and $Y^2$ is

 
 
 
 

13. When two variables more in the same direction then the correlation between the variable is

 
 
 
 

14. An investigator reports that the arithmetic mean of two regression coefficients of a regression line is 0.7 and the correlation coefficient is 0.75. Are the results

 
 
 
 

15. The geometric mean of the two regression coefficient $\beta_{YX}$ and $\beta_{XY}$ is equal to:

 
 
 
 

16. The estimate of $\beta$ in the regression equation $Y=\alpha+\beta\,X + e$ by the method of least square is:

 
 
 
 

17. The lines of regression intersect at the point

 
 
 
 

18. If $\beta_{YX}>1$, then $\beta_{XY}$ is:

 
 
 
 

19. If $\beta_{XY}$ and $\beta_{YX}$ are two regression coefficients, they have

 
 
 
 

20. If $X$ and $Y$ are two independent variates with variance $\sigma_X^2$ and $\sigma_Y^2$, respectively, the coefficient of correlation between $X$ and ($X-Y$) is equal to:

 
 
 
 


Correlation is a statistical measure used to determine the strength and direction of the mutual relationship between two quantitative variables. The regression describes how an explanatory variable is numerically related to the dependent variables.

Both of the tools are used to represent the linear relationship between the two quantitative variables. The relationship between variables can be observed either using a graphical representation between the variables or numerical computation using an appropriate computational formula.

MCQ Correlation and Regression

Note that neither regression nor correlation analyses can be interpreted as establishing some cause-and-effect relationships. Both of these can be used to indicate only how or to what extent the variables under study are associated (or mutually related) with each other. The correlation coefficient measures only the degree (strength) and direction of linear association between the two variables. Any conclusions about a cause-and-effect relationship must be based on the judgment of the analyst.

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32 thoughts on “Correlation and Regression 1”

  1. Q#2 wrong
    because
    Regression coefficient is independent of
    Both “Unit of measurement” and “Scale and origin”

    1. Thank you dear! for mentioning the error in quiz. More explanation is added to the question.
      If you find any other possible error in quiz or posts of itfeature.com, do let me know.

  2. Inbasat Masood

    sir these mcq’s are very useful but i dont find answers here , kindly tell me how to get añswer i m not getting even aftr submit

    1. When you press the show answer or next button correct answer is ticked with green color tick point. When you submit the complete quiz, you will get the results of all MCQs for the quiz after few seconds. If complete results are not shown it may be possible that you have some ade blocker plugin installed on your browser. Do allow the browser for the itfeature.com site.

  3. In the linear regression equation:

    Which variable is fixed and which one is random, between x & y ?

    1. The variable X and Y both are random in real sense. However, regarding the theory of least square, Variable X is assumed to be fixed (known). In other words, they (X’s) are assumed to have no random error. Also note that, in observational studies X is random while in experimental studies X is fixed.

    1. Can the correlation coefficient distinguish between the dependent and independent random variables with regards to question one?

      1. Correlation is a measure of strength between two quantitative variables. It measures the interdependence between these variables, so one cannot distinguish between the dependent and independent using only correlation coefficient.

          1. Nimra Shaheen

            Very helpful thanks sir!
            Sir kindly confirm these questions.
            In Exercise 1:Q3 is( b) option&Q4 is (a)

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