Squaring the Pearson correlation coefficient (r2) tells us that

Research was conducted on the amount of training for 5K race and the time a contestant took to run the race. The researcher recorded the number of miles a contestant ran during the last month of training and the time it took the contestant to complete the 5K. The results are below. Miles Trained 65 78 90 91 104 112 Time (Minutes) 23 26 34 39 42 50 (a) Give the correlation coefficient. Round to one decimal place. (b) Use technology to write the regression equation that predicts the time it takes a contestant to complete the race by using the miles trained as the explanatory variable. Complete the missing parts of the equation below, rounding values to one decimal place. ý (c) Interpret the y-intercept in the context of this scenario. O Each additional mile of training reduces the time needed to complete the 5K by 0.6 minutes. A contestant who has not trained at all in the last month can expect to complete the 5K in 0.6 minutes. X O A contestant who has not trained at all in the last…

Would A be the answer?

Research was conducted on the amount of training for 5K and the time a contestant took to run the race. The researcher recorded the number of miles during training ( a 1 month period) and the time to complete the 5K. The results are below. Miles Trained 45 77 37 25 60 64 Time (Minutes) 32.9 28 36.2 27.5 19.5 18.3 a) Give the correlation coefficient. r = b) Give the equation of the regression line. Round the values to 4 deimal places.This is in the form y = ax + b, so the slope goes in the first box and the y-inercept in the 2nd box.y = x + c) Interpret the y-intercept (Explain it's meaning, do not just give its value.)d) Predict the time in the 5K if someone trained 37 miles.Use the rounded values entered for the slope and intercept of the regression line to compute the predicted y-value.y = e) Give the residual for 37 miles trained.This is the actual y value for the runner who trained for miles minus the predicted value.Residual=