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.Data tabley =(Round to three decimal places as needed.)(b) Interpret the slope and y-intercept, if appropriate.Speed (mph)Distance (feet) D103.0393Begin by interpreting the slope.103.640298.0395O 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.100.8394O 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.101.4399O 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.105.4418O D. Interpreting the slope is not appropriate.101.2392101.7411Now interpret the y-intercept.101.3393103.3408O A. 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.103.5422O B. 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.104.8421O 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.(c) Predict the mean distance of all home runs hit at 103 mph.PrintDoneThe mean distance of all home runs hit at 103 mph isfeet.(Round to one decimal place as needed.)(d) If a ball was hit with a speed of 103 miles per hour, predict how far it will travel.If a ball is hit with a speed of 103 mph, the distance that it is most likely to travel is(Round to one decimal place as needed.)feet.Time Remaining: 03:57:09NextMacBook ProDIIDDB口888F9F10F11F7F4F5escF3F12ELeft 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.D. interpreting the siope is not appropriate.Critical values for the correlationNow interpret the y-intercept.O A. 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.Critical Values for Correlation CoefficieO B. 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 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.30.99740.950O D. Interpreting the y-intercept is not appropriate.0.8786.0.811(c) Predict the mean distance of all home runs hit at 103 mph.70.7548.0.707The mean distance of all home runs hit at 103 mph isfeet.0.666(Round to one decimal place as needed.)100.632(d) If a ball was hit with a speed of 103 miles per hour, predict how far it will travel.110.602120.576If a ball is hit with a speed of 103 mph, the distance that it is most likely to travel is(Round to one decimal place as needed.)feet.130.553140.532150.514(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.0.49716170.482farther than thefeet that would have been predicted given the speed with which the ball was hit.The ball180.468(Round to one decimal place as needed.)190.456200.444(f) Would you feel comfortable using the least-squares regression model on home runs where the speed of the ball was 122 mph? Explain.0.43321220.423O A. Yes, because the least squares regression model is the most accurate way to predict the distance of all home runs hit.0.41323240.404O B. 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.250.396C. 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.D. 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.PrintDoneDIIDDF12F10F11F9吕口F7F8F5F4F3F2LEDNescF1%232$34.5.62ELeft wtab

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