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 dataClick 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.(Round to three decimal places as needed.)(b) Interpret the slope and y-intercept, if appropriate.Begin by interpreting the slope.Data tableO 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 increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hit.Speed (mph) Distance (feet) OO C. 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 D. Interpreting the slope is not appropriate.110.4427105.5414101.4399Now interpret the y-intercept.100.7396103.5422O 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 distance that the ball would travel when the speed that the ball is hit is zero,OC. 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 hitO D. Interpreting the y-intercept is not appropriate101.7411103.640299.3394100,3392102.1392(c) Predict the mean distance of all home rus hit at 107 mph,105.4418101.2392The mean distance of all home runs hit at 107 mph is feet(Round to one decimal place as needed.)(d) If a ball was hit with a speed of 107 miles per hour, predict how far it will travel.PrintDoneIf a ball is hit with a speed of 107 mph, the distance that it is most likely to travel is feet.(Round to one decimal place as needed)(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.The ballV farther than the feet that would have been predicted given the speed with which the ball was hit.(Round to one decimal place as needed)(1) Would you feel comfortable using the least-squares regression model on home runs where the speed of the ball was 122 mph? ExplainO A. 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.TATCOA2334403LI 10&-201MAINTOBAZ330AD 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 basebal game in 2018. Complete parts (a) through (1).Click here to view the data,Click here to view the critical.valu0s of the correlation coefficient.***.(b) Interpret the slope and y-Intercept, if appropriate.Critical values for the correlation coefficientBegin 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 increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hitCritical Values for Correlation CoefficientOC. 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 zeroO D. Interpreting the slope is not appropriate.3.0.99740.950Now interpret the y-intercept.08786.0.811O 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 distance that the ball would travel when the speed that the ball is hit is zero,70.75480.70790.666O C. 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 hit100.632O D. Interpreting the y-Intercept is not appropriate0.602120.576(c) Predict the mean distance of all home runs hit at 107 mph.130.553The mean distance of all home runs hit at 107 mph is fet.(Round to one decimal place as needed)140.532150.514160.497(d) IH a ball was hit with a speed of 107 miles per hour, predict how far it will travel170.482If a bal is hit with a speed of 107 mph, the distance that it is most likely to travel is feet(Round to one decimal place as needed.)180.4680.45619200.444(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? Explain21220.4330.423The ballfarther than the teet that would have been predicted given the speed with which the ball was hit.230.413(Round to one decimal place as needed.)240404() Would you feel comfortable using the least-squares regression model on home runs where the speed of the ball was 122 mph? Explain.250.396260388O A. 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 B. Yes, because the least squares regression model is the most accurate way to predict the distance of all home runs hit.OC. 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 modelOD. 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.270.381280.374290.367300.361PrintDoneO TimeTCOA2334403U 108-2014MAINTCGA233DARA

Name: The following data represent the speed at which a ball was hit (in mi
Uploaded: 2022-11-23T13:49:28.000Z
Channel: Bartleby
Description: 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

Since you have posted a question with multiple sub-parts, we will solve first three sub- parts for you. To get remaining sub-part solved please repost the complete question and mention the sub-parts to be solved. (a) Use EXCEL to determine the regression equation. EXCEL procedure: Go to EXCEL Go to Data>Data Analysis. Choose Regression. Input Y range as $A$1:$A$13. Input X range as $B$1:$B$13. Check the option Labels in First row. Click OK. EXCEL output: From the EXCEL output, the regression equation is, (b) Interpret the slope. The slope is interpreted below as follows: The value of slope is 3.499. That is, for every additional mile increase in speed the Distance of the speed of ball is predicted to increase on an average of 3.499 feet Correct option: Option A Interpret the intercept. The intercept is interpreted below as follows: The value of intercept is 44.744 That is, if the Distance of the speed of ball equals 0 miles in hour then the Distance of the speed of ball equals 44.744. Correct option: Option B(c ) Predict the mean distance of all home runs hit at 107 mph. Sub x=107 in regression equation. Thus, the Predicted value of the mean distance of all home runs hit at 107 mph is 419.1.

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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. (Round to three decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. Begin by interpreting the slope. - X Data table 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 increase in the speed that the ball was hit with every 1 foot increase in the distance that the ball was hit. Speed (mph) Distance (feet) o O C. 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. 110.4 427 O D. Interpreting the slope is not appropriate. 105.5 414 101.4 399 Now interpret the y-intercept 100.7 396 103.5 422 O 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 distance that the ball would travel when the speed that the ball is hit is zero. O C. 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 D. Interpreting the y-Intercept is not appropriate 101.7 411 103.6 402 99.3 394 100.3 392 102.1 392 (c) Predict the mean distance of al home runs hit at 107 mph, 105.4 418 101.2 392 The mean distance of all home runs hit at 107 mph is feet (Round to one decimal place as needed)