biX, the slope coefficient b1 represents 11. In the standard regression Y bo A.

Question

biX, the slope coefficient b1 represents 11. In the standard regression Y bo A. The average value of Y when X equals 0 B. The expected change in Y per unit change in X C. The expected change in X per unit change in Y D. The average value of X when Y equals 0 12. Given a normal distribution with mean = 50 and standard deviation-4, between what two X values (symmetrically distributed around the mean) are 60% of the values? A. 46.64 and 53.36 B. 44.68 and 55.32 C. 42.16 and 57.84 D. 44.88 and 55.12 includes all values from the smallest to the largest X used in developing the 13. The regression model A. extrapolation parameter B. sum of squares interval C. relevant range D. coefficient of determination 14. In a regression, the residual is A. also called the error B. the difference between the actual (observed) value of Y and the predicted value of C. The difference between the average value of Y and the average value of X D. Both A and B 15. Which statistician is most associated with the development of regression? A. Gosset B. Pearson C. Carlson D. Gauss 16. The level of significance of the test is: A. The probability of rejecting the null hypothesis when the null hypothesis is true. B. Usually symbolized by the Greek letter alpha C. The probability of a Type I error D. All of the above 17. Errors in regression fanning out with larger values of X is a condition called A. Serendipity B. Multicollinearity C. Autocorrelation D. Heteroscedascity 18. In terms of the errors (or residuals), one of the standard assumptions of regression analysis is that they exhibit: A. Multicollinearity B. Heteroscedasticity C. Normality D. Autocorrelation 19. If the Durbin-Watson statistic has a value close to 0, which assumption is violated? A. B. C. Normality of errors Homoscedasticity Independence of errors (and if the value is close to O then the problem of autocorrelation is present) D. None of the above

Explanation / Answer

(11) In the standard regression y=b0+b1X the slope coefficient b1 represents
Ans: The expected change in Y per unit change in X
(option B is correct)

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