ee questions (17 to 19) refer to the following: We would like to examine how the speed of a professional baseball player can be used to predict his power. Two important statistics in baseball are home runs and stolen bases. Strong hitters will hit many home runs, and fast runners will steal many bases. A random sample of 20 Major League Baseball players is selected, and the number of bases X the player stole and the number of home runs Y the player hit last season are recorded. The equation of the least squares regression line is calculated to be y = 35.19 - 0.781. It is also determined that 61.9% of the variation in number of home runs hit can be accounted for by its regression on number of stolen bases. 17. What is the correct interpretation of the slope of the least squares regression line? (A) When the number of stolen bases increases by one, we predict an increase of 0.78 home runs. (B) When the number of home runs increases by one, we predict a decrease of 0.78 stolen bases. (C) When the number of stolen bases increases by 0.78, we predict a decrease of one home run. D) When the number of home runs increases by 0.78, we predict a decrease of one stolen base. (E) When the number of stolen bases increases by one, we predict a decrease of 0.78 home runs. 18. What is the correlation between number of stolen bases Ind number of home runs? (A) 0.787 (B) -0.619 (C) -0.352 (D) 0.619 (E) -0.787 19. One player in the sample hit 4 home runs and had a residual of -7.79. How many stolen bases did this player have? (A) 28 (B) 30 (C) 32 (D) 35 (E) 40