If the correlation coefficient is a positive value, then the slope of the regression line

Related MCQs

• Regression analysis was applied to return rates of sparrowhawk colonies. Regression analysis was used to study the relationship between return rate (x: % of birds that return to the colony in a given year) and immigration rate (y: % of new adults that join the colony per year). The following regression equation was obtained. $$$ \hat{y} = 31.9 - 0.34x$$ Based on the above estimated regression equation, if the return rate were to decrease by 10% the rate of immigration to the colony would:
• Suppose the correlation coefficient between height (as measured in feet) versus weight (as measured in pounds) is 0.40. What is the correlation coefficient of height measured in inches versus weight measured in ounces? [12 inches = one foot; 16 ounces = one pound]
• If the coefficient of determination is a positive value, then the regression equation
• If there is a very strong correlation between two variables then the correlation coefficient must be
• If the coefficient of determination is equal to 1, then the correlation coefficient
• This question is related to questions 4 and 21 above. The relationship between number of beers consumed (x) and blood alcohol content (y) was studied in 16 male college students by using least squares regression. The following regression equation was obtained from this study: $$$ \hat{y} = -0.0127 + 0.0180x$$ Another guy, his name Dudley, has the regression equation written on a scrap of paper in his pocket. Dudley goes out drinking and has 4 beers. He calculates that he is under the legal limit (0.08) so he decides to drive to another bar. Unfortunately Dudley gets pulled over and confidently submits to a road-side blood alcohol test. He scores a blood alcohol of 0.085 and gets himself arrested. Obviously, Dudley skipped the lecture about residual variation. Dudley’s residual is:
• Suppose that you have carried out a regression analysis where the total variance in the response is 133452 and the correlation coefficient was 0.85. The residual sums of squares is:
• If the coefficient of determination is 0.81, the correlation coefficient
• In a regression and correlation analysis if r2 = 1, then
• Regression analysis was applied between $ sales (y) and $ advertising (x) across all the branches of a major international corporation. The following regression function was obtained. $$$ \hat{y} = 5000 + 7.25x$$ If the advertising budgets of two branches of the corporation differ by $30,000, then what will be the predicted difference in their sales?