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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 66 71 83 100 110 110 Time (Minutes) 23 27 35 35 45 47 (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. y = (c) Interpret the y-intercept in the context of this scenario. Each additional mile of training reduces the time needed to complete the 5K by 0.5 minutes. A contestant who has not trained at all in the last month can expect to complete the 5K in -6.7 minutes. Each additional mile of training reduces the time needed to complete the 5K by -6.7 minutes. A contestant who has not trained at all in the last month can expect to complete the 5K in 0.5 minutes. x

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 66 71 83 100 110 110 Time (Minutes) 23 27 35 35 45 47 (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. y = (c) Interpret the y-intercept in the context of this scenario. Each additional mile of training reduces the time needed to complete the 5K by 0.5 minutes. A contestant who has not trained at all in the last month can expect to complete the 5K in -6.7 minutes. Each additional mile of training reduces the time needed to complete the 5K by -6.7 minutes. A contestant who has not trained at all in the last month can expect to complete the 5K in 0.5 minutes. x

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 15PPS
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B 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 66 71 83 100 110 110 Time (Minutes) 23 27 35 35 45 47 (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. y = (c) Interpret the y-intercept in the context of this scenario. Each additional mile of training reduces the time needed to complete the 5K by 0.5 minutes. A contestant who has not trained at all in the last month can expect to complete the 5K in -6.7 minutes. Each additional mile of training reduces the time needed to complete the 5K by -6.7 minutes. A contestant who has not trained at all in the last month can expect to complete the 5K in 0.5 minutes. + (d) Use your answer from part (b) to predict the time needed to complete the 5K if a runner trained 100 miles last month. Round to one decimal place. minutes
Transcribed Image Text:B 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 66 71 83 100 110 110 Time (Minutes) 23 27 35 35 45 47 (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. y = (c) Interpret the y-intercept in the context of this scenario. Each additional mile of training reduces the time needed to complete the 5K by 0.5 minutes. A contestant who has not trained at all in the last month can expect to complete the 5K in -6.7 minutes. Each additional mile of training reduces the time needed to complete the 5K by -6.7 minutes. A contestant who has not trained at all in the last month can expect to complete the 5K in 0.5 minutes. + (d) Use your answer from part (b) to predict the time needed to complete the 5K if a runner trained 100 miles last month. Round to one decimal place. minutes
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