Muhammad Imdad Ullah

The post is about the Correlation and Regression Quiz. There are 20 multiple-choice questions. The quiz covers the topics related to correlation analysis and regression analysis, Basic concepts, assumptions, and violations of correlation and regression analysis, Model selection criteria, interpretation of correlation and regression coefficients, etc.

Online MCQs about Correlation and Regression Analysis with Answers

1. To determine the height of a person when his weight is given is

 Association problem

 Correlation problem

 Regression problem

 Anova probelm

2. The relationship between the correlation coefficient and the coefficient of determination is that

 The coefficient of determination is the square root of the coefficient of correlation

 Both are equal

 The coefficient of determination is the coefficient of correlation squared

 Both are unrelated

3. In the straight line graph of the linear equation $Y=a+bX$, the slope will be upward if

 $b\ne0$

 $b < 0$

 $b>0$

 $b=0$

4. The dependent variable is also called

 Continuous variable

 Explanatory variable

 Regressor

 Regressand

5. What test statistic is used for a global test of significance?

 t-test

 F-test

 Z-test

 Chi-square test

6. The strength (degree) of the correlation between a set of independent variables $X$ and a dependent variable $Y$ is measured by

 All of the above

  Coefficient of Correlation

 Coefficient of Determination

 Standard error of estimate

7. If $\beta_{yx} = -1.36$ and $\beta_{xy} = -0.34$ then $r_{xy} =$

 0.46

 0.21

 0.68

 -0.68

8. Multicollinearity exists when

 The relationship between the dependent and independent variable is non-linear

 There is only one independent variable

 An independent variable is strongly correlated with a dependent variable

 Independent variables are correlated less than -0.70 or more than 0.70

9. If “time” is used as the independent variable in a simple linear regression analysis, then which of the following assumptions could be violated

 There is a linear relationship between the independent and dependent variables

 The residuals are normally distributed

 The residual variation is the same for all fitted values of Y

 Successive observations of the dependent variable are uncorrelated

10. The dependent variable is also called

 Regressand variable

 All of the options

 Predictand variable

 Explained variable

11. A residual is defined as

 Regression Sum of Squares

 Error Sum of Square

 Type I Error

 $ Y−\hat{Y} $

12. In the straight line graph of the linear equation $Y=a+bX$, the slope will be downward if

 $b\ne0$

 $b=0$

 $b < 0$

 $b>0$

13. In multiple regression, when the global test of significance is rejected, we can conclude that

 All of the net sample regression coefficients are equal to zero

 All of the sample regression coefficients are not equal to zero

 The regression equation intersects the Y-axis at zero.

 At least one sample regression coefficient is not equal to zero

14. For the regression $\hat{Y}=5$, the value of regression coefficient of $Y$ on $X$ will be

 0.5

 1

 5

 0

15. The percent of the total variation of the dependent variable $Y$ explained by the set of independent variables $X$ is measured by

 Coefficient of Determination

  Coefficient of Correlation

 Coefficient of Skewness

 Standard Error of Estimate

 Multicollinearity

16. If the value of any regression coefficient is zero, then two variables are said to be

 Independent

 Dependent

 Qualitative

 Correlated

17. A coefficient of correlation is computed to be -0.95 means that

 The relationship between the two variables is strong and positive

 The relationship between the two variables is strong and but negative

 The correlation coefficient cannot have this value

 The relationship between the two variables is weak

18. In the straight line graph of the linear equation $Y=a+BX$, the slope is horizontal if

 $b=1$

 $b\ne0$

 $a=b$

 $b=0$

19. Let the coefficient of determination computed to be 0.39 in a problem involving one independent variable and one dependent variable. This result means that

 The relationship between the two variables is negative

 The correlation coefficient is 0.39 also

 39% of the total variation is explained by the dependent variable

 39% of the total variation is explained by the independent variable

20. If one regression coefficient is greater than one then the other will be

 Equal to minus one

 More than one

 Equal to one

 Less than one

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Online Correlation and Regression Quiz with Answers

• The strength (degree) of the correlation between a set of independent variables $X$ and a dependent variable $Y$ is measured by
• The percent of the total variation of the dependent variable $Y$ explained by the set of independent variables $X$ is measured by
• A coefficient of correlation is computed to be -0.95 means that
• Let the coefficient of determination computed to be 0.39 in a problem involving one independent variable and one dependent variable. This result means that
• The relationship between the correlation coefficient and the coefficient of determination is that
• Multicollinearity exists when
• If “time” is used as the independent variable in a simple linear regression analysis, then which of the following assumptions could be violated
• In multiple regression, when the global test of significance is rejected, we can conclude that
• A residual is defined as
• What test statistic is used for a global test of significance?
• If the value of any regression coefficient is zero, then two variables are said to be
• In the straight line graph of the linear equation $Y=a+bX$, the slope will be upward if
• In the straight line graph of the linear equation $Y=a+bX$, the slope will be downward if
• In the straight line graph of the linear equation $Y=a+BX$, the slope is horizontal if
• For the regression $\hat{Y}=5$, the value of regression coefficient of $Y$ on $X$ will be
• If $\beta_{yx} = -1.36$ and $\beta_{xy} = -0.34$ then $r_{xy} =$
• If one regression coefficient is greater than one then the other will be
• To determine the height of a person when his weight is given is
• The dependent variable is also called
• The dependent variable is also called

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The post is about Correlation and Regression MCQs. There are 20 multiple-choice questions. The quiz covers topics related to the basics of correlation Analysis and regression analysis, correlation and regression coefficients, graphical representation relationships between variables, simple linear regression models and multiple linear regression models, and assumptions related to correlation and regression models. Let us start with the Correlation and Regression MCQs Quiz.

Please go to Best Correlation and Regression MCQs 1 to view the test

Online Correlation and Regression MCQs

• The estimate of $\beta$ in the regression equation $Y=\alpha+\beta\,X + e$ by the method of least square is:
• If $\beta_{XY}$ and $\beta_{YX}$ are two regression coefficients, they have
• The average of two regression coefficients is always greater than or equal to the correction coefficient is called:
• If $\beta_{YX}>1$, then $\beta_{XY}$ is:
• If the two lines of regression are perpendicular to each other, the correlation coefficient $r=$ is:
• The regression coefficient is independent of
• If each of $X$ variable is divided by 5 and $Y$ by 10 then $\beta_{YX}$ by coded value is:
• The geometric mean of the two regression coefficient $\beta_{YX}$ and $\beta_{XY}$ is equal to:
• 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:
• In multiple linear regression analysis, the square root of Mean Squared Error (MSE) is called the:
• The range of a partial correlation coefficient is:
• Homogeneity of three or more population correlation coefficients can be tested by
• If $\rho$ is the correlation coefficient, the quantity $\sqrt{1-\rho^2}$ is termed as
• If the correlation coefficient between the variables $X$ and $Y$ is $\rho$, the correlation coefficient between $X^2$ and $Y^2$ is
• The lines of regression intersect at the point
• If $\rho=0$, the lines of regression are:
• 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
• If regression line $\hat{y}=5$ then value of regression coefficient of $y$ on $x$ is
• When two variables move in the same direction then the correlation between the variables is
• If all the actual and estimated values of $Y$ are the same on the regression line, the sum of squares of errors will be

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