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GR P Pasha, asha, CHAPTER NO 6 1. The major difference between regression analysis and correlation analysis is that in regression analysis: The independent vvariable ariable is known without error error.. 2. The term homoscedasticity refers to : Equal variance of the depen dependent dent variable , Y Y,, for any vvalue alue of independent variable , X. 3. The sum of squares of which type of deviations is minimized by the least square regression: Deviations of the vvalues alues of the dependent vvar ar ariable iable fro from m the line. 4. A random sample of paired observations has been selected and the sample correlation coefficient has been found to be -1. From this result we know that:: all sample observations lie on the sample rregression egression line. 5. What information is given by a value of the coefficient of determination: Strength of relationship relationship. 6. The correlation coefficient: equals the positive or negative ssquare quare root of the coefficient of determination determination. 7. The estimated regression line relating the market value of a person’s stock portfolio to his annual income is

^ Y =5000+ 0.10 X . This means that each additional rupee of

income will increase the stock portfolio by: Rs. 0.10 8. Which one of the following situations is inconsistent:

^ Y =−200+ 0.9 X ,∧r =−0.86

9. Which one of the following statements is true? The units in which X and Y are measured will not affect the value of rr.. 10. The true correlation coefficient

ρ

will be zero only if. The slope of the true regressi regression on

line is equal to zero. 11. In Regression analysis the relation between x and y is assumed to be : linear 12. Coefficient of determination is equal to: The Square of the correlation coefficient. The Proportion of variation in Y explained by regression. 1 minus the proportion of variation in Y unexplained by regression. All 13. The coefficient of partial determination differs from the coefficient of multiple determination in that: one may be negative negative,, but the other is alwa always ys positive. 14. The coefficient of multiple determination is 0.81. Thus the multiple correlation coefficient is: 0.9 15. A larger sample size can be expected to achieve all but which one not of the following? A smaller value for standard error of regression. Increase degrees of freedom. An estimated regression plane that is closer to the true regression plane. Increase in the value o off coefficien coefficientt of determination. 16. In multiple linear regression analysis, the square root of mean square error (MSE) is called: Standard error of estimate. 17. In multiple linear regression analysis, the purpose of solving the normal equations is to find: the constant and coefficien coefficients ts in the least square rrelationship. elationship....