1. If the regression equation is a perfect estimator of the dependent variable then which of the following is not true ?

2. The extent to which the observed values of the depended variable differ from the predicted values according to the regression line is measured by-

3. If the co-variance between two variables is positive then, the coefficient of correlation between them will be in the range of-

4. The variances of variables, x and y, are 49 and 16 respectively, and the covariance between them is 14. What is the coefficient of correlation between x and y ?

5. For a simple linear regression equation Σ(y – ŷ)² = 256 and the standard error of estimate is 4. What is the number of observations ?

6. The regression relationship between the variables x and y is given by ŷ = 4 + 5 x and, it explain 64% of the changes in the variable y. What is the coefficient of correlation between x and y ?

7. Which of the following is correct with regard to the method of least squares used in simple regression analysis ?

8. If a regression line is represented by Y = 1.5 – 2.0x and the coefficient of determination is 0.49, then the coefficient of correlation is

9. If the variance of x and y are 2.56 and 6.25 respectively, and the covariance between them is 3.20 then the coefficient of correlation between x and y is-

10. The standard error of estimate is developed from the variations of the