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The following data represent the speed at which a ball was hit (in miles per hour) and the distance it traveled (in feet) for a random sample of home runs in a Major League baseball game in 2018. Complete parts (a) through (n. Click here to view the data Click here to view the critical values of the correlation.coefficient. (a) Find the least-squares regression line treating speed at which the ball was hit as the explanatory variable and distance the ball traveled as the response variable. y = 0x+ (0) (Round to three decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. Begin by interpreting the slope. O A. The slope of this least-squares regression line says that the distance the ball travels increases by the slope with every 1 mile per hour increase in the speed that the ball was hit. O B. The slope of this least-squares regression line shows the distance that the ball would travel when the speed that the ball is hit is zero. O C. The slope of this least-squares regression line shows the increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hit. O D. Interpreting the slope is not appropriate. Now interpret the y-intercept. A. The y-intercept of this least-squares regression line shows the speed that the ball is hit at when the distance that the ball travels is zero. O B. The y-intercept of this least-squares regression line shows the increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hit. OC. The y-intercept of this least-squares regression line shows the distance that the ball would travel when the speed that the ball is hit is zero. D. Interpreting the y-intercept is not appropriate. (c) Predict the mean distance of all home runs hit at 105 mph. The mean distance of all home nuns hit at 105 moh is lol feet (A) More O Time Remaining: 03:35:27 Submit test DEC 15 étv J MacBook Air DII DO 80 F12 esc F9 F10 F2 F4 FS F6 F7 F1

The following data represent the speed at which a ball was hit (in miles per hour) and the distance it traveled (in feet) for a random sample of home runs in a Major League baseball game in 2018. Complete parts (a) through (n. Click here to view the data Click here to view the critical values of the correlation.coefficient. (a) Find the least-squares regression line treating speed at which the ball was hit as the explanatory variable and distance the ball traveled as the response variable. y = 0x+ (0) (Round to three decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. Begin by interpreting the slope. O A. The slope of this least-squares regression line says that the distance the ball travels increases by the slope with every 1 mile per hour increase in the speed that the ball was hit. O B. The slope of this least-squares regression line shows the distance that the ball would travel when the speed that the ball is hit is zero. O C. The slope of this least-squares regression line shows the increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hit. O D. Interpreting the slope is not appropriate. Now interpret the y-intercept. A. The y-intercept of this least-squares regression line shows the speed that the ball is hit at when the distance that the ball travels is zero. O B. The y-intercept of this least-squares regression line shows the increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hit. OC. The y-intercept of this least-squares regression line shows the distance that the ball would travel when the speed that the ball is hit is zero. D. Interpreting the y-intercept is not appropriate. (c) Predict the mean distance of all home runs hit at 105 mph. The mean distance of all home nuns hit at 105 moh is lol feet (A) More O Time Remaining: 03:35:27 Submit test DEC 15 étv J MacBook Air DII DO 80 F12 esc F9 F10 F2 F4 FS F6 F7 F1

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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The following data represent the speed at which a ball was hit (in miles per hour) and the distance it traveled (in feet) for a random sample of home runs in a Major League baseball game in 2018. Complete parts (a) through (f). Click here to view the data. Click here to view the critical values of the correlation coefficient. ..... (a) Find the least-squares regression line treating speed at which the ball was hit as the explanatory variable and distance the ball traveled as the response variable. y = 0x+(0) (Round to three decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. Begin by interpreting the slope. A. The slope of this least-squares regression line says that the distance the ball travels increases by the slope with every 1 mile per hour increase in the speed that the ball was hit. O B. The slope of this least-squares regression line shows the distance that the ball would travel when the speed that the ball is hit is zero. O C. The slope of this least-squares regression line shows the increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hit. O D. Interpreting the slope is not appropriate. Now interpret the y-intercept. A. The y-intercept of this least-squares regression line shows the speed that the ball is hit at when the distance that the ball travels is zero. O B. The y-intercept of this least-squares regression line shows the increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hit. O C. The y-intercept of this least-squares regression line shows the distance that the ball would travel when the speed that the ball is hit is zero. O D. Interpreting the y-intercept is not appropriate. (c) Predict the mean distance of all home runs hit at 105 mph. The mean distance of all home runs hit at 105 mph is 10l feet. 1, (1,1) More O Time Remaining: 03:35:27 Submit test 1 DEC étv 15 280 PD MacBook Air DII 80 esc F7 F8 F9 F10 F11 F12 F2 F3 F4 F5 F6 F1 C@ %23 %24 % & 1 4 5 7 8 9 { Q W E Y P + I/ R #3 ©2
Transcribed Image Text:The following data represent the speed at which a ball was hit (in miles per hour) and the distance it traveled (in feet) for a random sample of home runs in a Major League baseball game in 2018. Complete parts (a) through (f). Click here to view the data. Click here to view the critical values of the correlation coefficient. ..... (a) Find the least-squares regression line treating speed at which the ball was hit as the explanatory variable and distance the ball traveled as the response variable. y = 0x+(0) (Round to three decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. Begin by interpreting the slope. A. The slope of this least-squares regression line says that the distance the ball travels increases by the slope with every 1 mile per hour increase in the speed that the ball was hit. O B. The slope of this least-squares regression line shows the distance that the ball would travel when the speed that the ball is hit is zero. O C. The slope of this least-squares regression line shows the increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hit. O D. Interpreting the slope is not appropriate. Now interpret the y-intercept. A. The y-intercept of this least-squares regression line shows the speed that the ball is hit at when the distance that the ball travels is zero. O B. The y-intercept of this least-squares regression line shows the increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hit. O C. The y-intercept of this least-squares regression line shows the distance that the ball would travel when the speed that the ball is hit is zero. O D. Interpreting the y-intercept is not appropriate. (c) Predict the mean distance of all home runs hit at 105 mph. The mean distance of all home runs hit at 105 mph is 10l feet. 1, (1,1) More O Time Remaining: 03:35:27 Submit test 1 DEC étv 15 280 PD MacBook Air DII 80 esc F7 F8 F9 F10 F11 F12 F2 F3 F4 F5 F6 F1 C@ %23 %24 % & 1 4 5 7 8 9 { Q W E Y P + I/ R #3 ©2
The following data represent the speed at which a ball was hit (in miles per hour) and the distance it traveled (in feet) for a random sample of home runs in a Major League baseball game in 2018. Complete parts (a) through (f). Click here to view the data. Click here to view the critical values of the correlation coefficient. Data table A. The y-intercept of this least-squares regression line shows the speed that the ball is hit at when the distance that the ball travels is zero. O B. The y-intercept of this least-squares regression line shows the increase in the speed that the ball was hit with every 1 foot increase in the distance that the b Speed (mph) Distance (feet) 3 O C. The y-intercept of this least-squares regression line shows the distance that the ball would travel when the speed that the ball is hit is zero. 100.8 394 O D. Interpreting the y-intercept is not appropriate. 101.7 411 99.3 394 (c) Predict the mean distance of all home runs hit at 105 mph. 103.5 395 The mean distance of all home runs hit at 105 mph is 0 feet. 105.4 418 (Round to one decimal place as needed.) 101.4 399 110.4 427 (d) If a ball was hit with a speed of 105 miles per hour, predict how far it will travel. 103.5 422 If a ball is hit with a speed of 105 mph, the distance that it is most likely to travel is 0 feet. (Round to one decimal place as needed.) 107.9 441 102.1 392 103.4 394 (e) Christian Yelich hit a home run 398 feet. The speed at which the ball was hit was 106.2 mph. Did this ball travel farther than you would have predicted? Explain. 101.2 392 The ball traveled farther than the 0 feet that would have been predicted given the speed with which the ball was hit. (Round to one decimal place as needed.) (f) Would you feel comfortable using the least-squares regression model on home runs where the speed of the ball was 122 mph? Explain. Print Done A. No, because the least squares regression model can accurately predict the distance of home runs with a lower speed than was observed, but not higher. B. Yes, because the least squares regression model can accurately predict the distance of home runs with a higher speed than was observed, but not lower. O C. No, because the least squares regression model cannot predict the distance of a home run when the speed of the ball is outside of the scope of the model. O D. Yes, because the least squares regression model is the most accurate way to predict the distance of all home runs hit. O Time Remaining: 03:33:47 Submit test 1 DEC étv 15 280 MacBook Air DII 80 esc F9 F10 F11 F12 F3 F4 F5 F6 F7 F8 F1 F2 %23 $ & 2 3 4 5 6 7 8 9 } { [ Q W E Y P * 00 T R LO
Transcribed Image Text:The following data represent the speed at which a ball was hit (in miles per hour) and the distance it traveled (in feet) for a random sample of home runs in a Major League baseball game in 2018. Complete parts (a) through (f). Click here to view the data. Click here to view the critical values of the correlation coefficient. Data table A. The y-intercept of this least-squares regression line shows the speed that the ball is hit at when the distance that the ball travels is zero. O B. The y-intercept of this least-squares regression line shows the increase in the speed that the ball was hit with every 1 foot increase in the distance that the b Speed (mph) Distance (feet) 3 O C. The y-intercept of this least-squares regression line shows the distance that the ball would travel when the speed that the ball is hit is zero. 100.8 394 O D. Interpreting the y-intercept is not appropriate. 101.7 411 99.3 394 (c) Predict the mean distance of all home runs hit at 105 mph. 103.5 395 The mean distance of all home runs hit at 105 mph is 0 feet. 105.4 418 (Round to one decimal place as needed.) 101.4 399 110.4 427 (d) If a ball was hit with a speed of 105 miles per hour, predict how far it will travel. 103.5 422 If a ball is hit with a speed of 105 mph, the distance that it is most likely to travel is 0 feet. (Round to one decimal place as needed.) 107.9 441 102.1 392 103.4 394 (e) Christian Yelich hit a home run 398 feet. The speed at which the ball was hit was 106.2 mph. Did this ball travel farther than you would have predicted? Explain. 101.2 392 The ball traveled farther than the 0 feet that would have been predicted given the speed with which the ball was hit. (Round to one decimal place as needed.) (f) Would you feel comfortable using the least-squares regression model on home runs where the speed of the ball was 122 mph? Explain. Print Done A. No, because the least squares regression model can accurately predict the distance of home runs with a lower speed than was observed, but not higher. B. Yes, because the least squares regression model can accurately predict the distance of home runs with a higher speed than was observed, but not lower. O C. No, because the least squares regression model cannot predict the distance of a home run when the speed of the ball is outside of the scope of the model. O D. Yes, because the least squares regression model is the most accurate way to predict the distance of all home runs hit. O Time Remaining: 03:33:47 Submit test 1 DEC étv 15 280 MacBook Air DII 80 esc F9 F10 F11 F12 F3 F4 F5 F6 F7 F8 F1 F2 %23 $ & 2 3 4 5 6 7 8 9 } { [ Q W E Y P * 00 T R LO
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