Correlation and Regression 1

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

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

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

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

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

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

7. 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

8. Regression coefficient is independent of

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

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

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

12. The lines of regression intersect at the point

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

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

15. 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:

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

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

18. The range of a partial correlation coefficient is:

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

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