:he regression line to go through the origin). Derive an expression 1eX,-'s and K's) for ,8 in this case. :ennis ball straight up in the air. The table below shows the :measured in feet from the ground) at n=7 times, measured in 1e=0 corresponds to the time at which the ball was released. above data by the linear regression model: Yr=)fi'o\"l~;(5'1}a+ea5 :ight and X is Time, obtain the numerical values for the least Ltes ofBo and 31. he model fit in (a), the Pearson correlation betweenX and Y is :son claims that this makes perfect sense, because the regression :l in (a) has an estimated slope of zero, so no matter what the .s, the best prediction of height is a constant. That is to say, rant for predicting Height for this model. Another person claims : must have been made in the calculations of part (a), since there .t the height of the ball could be independent of elapsed time. : explanation to resolve this dispute