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following data represent the commute time (in minutes) x and a score on well-being survey y. The equation of the least-squares regression line is y nd the standard error of the estimate is 0.5157. Complete parts (a) through (e) below. X y 5 25 35 50 72 105 15 69.0 68.2 67.4 67.1 66.8 66.5 63.6 (...) a) Predict the mean well-being index composite score of all individuals whose commute time is 20 minutes. = (Round to two decimal places as needed.) b) Construct a 90% confidence interval for the mean well-being index composite score of all individuals whose commute time is 20 minutes. Lower Bound (Round to two decimal places as needed.) Upper Bound = (Round to two decimal places as needed.) = c) Predict the well-being index composite score of Jane, whose commute time is 20 minutes. = (Round to two decimal places as needed.) d) Construct a 90% prediction interval for the well-being index composite score of Jane, whose commute time is 20 minutes. 0400X 00.

following data represent the commute time (in minutes) x and a score on well-being survey y. The equation of the least-squares regression line is y nd the standard error of the estimate is 0.5157. Complete parts (a) through (e) below. X y 5 25 35 50 72 105 15 69.0 68.2 67.4 67.1 66.8 66.5 63.6 (...) a) Predict the mean well-being index composite score of all individuals whose commute time is 20 minutes. = (Round to two decimal places as needed.) b) Construct a 90% confidence interval for the mean well-being index composite score of all individuals whose commute time is 20 minutes. Lower Bound (Round to two decimal places as needed.) Upper Bound = (Round to two decimal places as needed.) = c) Predict the well-being index composite score of Jane, whose commute time is 20 minutes. = (Round to two decimal places as needed.) d) Construct a 90% prediction interval for the well-being index composite score of Jane, whose commute time is 20 minutes. 0400X 00.

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 commute time (in minutes) x and a score on a well-being survey y. The equation of the least-squares regression line is y=-0.0468x + 68.9967 and the standard error of the estimate is 0.5157. Complete parts (a) through (e) below. X 5 T y 69.0 Lower Bound Upper Bound 15 25 35 50 72 105 68.2 67.4 67.1 66.8 66.5 63.6 (a) Predict the mean well-being index composite score of all individuals whose commute time is 20 minutes. y= (Round to two decimal places as needed.) (b) Construct a 90% confidence interval for the mean well-being index composite score of all individuals whose commute time is 20 minutes. = (Round to two decimal places as needed.) = (Round to two decimal places as needed.) G (c) Predict the well-being index composite score of Jane, whose commute time is 20 minutes. y= (Round to two decimal places as needed.) (d) Construct a 90% prediction interval for the well-being index composite score of Jane, whose commute time is 20 minutes. Lower Bound (Round to two decimal places as needed.) Upper Bound (Round to two decimal places as needed.) (e) What is the difference between the predictions made in parts (a) and (c)? = = O A. The prediction made in part (a) is an estimate of the mean well-being score for all individuals whose commute is 20 minutes, and the prediction made in part (c) is an estimate of the well-being score for the individual, Jane, whose commute is 20 minutes. O B. The prediction made in part (a) is the average well-being score for all individuals whose commute is 68.06 minutes, and the prediction made in part (c) is an estimate of the well-being score for the individual, Jane, whose commute is 68.06 minutes. O C. The prediction made in part (a) is an estimate of the well-being score for the individual, Jane, whose commute is 20 minutes, and the prediction made in part (c) is an estimate of the mean well-being score for all individuals whose commute is 20 minutes.
Transcribed Image Text:The following data represent the commute time (in minutes) x and a score on a well-being survey y. The equation of the least-squares regression line is y=-0.0468x + 68.9967 and the standard error of the estimate is 0.5157. Complete parts (a) through (e) below. X 5 T y 69.0 Lower Bound Upper Bound 15 25 35 50 72 105 68.2 67.4 67.1 66.8 66.5 63.6 (a) Predict the mean well-being index composite score of all individuals whose commute time is 20 minutes. y= (Round to two decimal places as needed.) (b) Construct a 90% confidence interval for the mean well-being index composite score of all individuals whose commute time is 20 minutes. = (Round to two decimal places as needed.) = (Round to two decimal places as needed.) G (c) Predict the well-being index composite score of Jane, whose commute time is 20 minutes. y= (Round to two decimal places as needed.) (d) Construct a 90% prediction interval for the well-being index composite score of Jane, whose commute time is 20 minutes. Lower Bound (Round to two decimal places as needed.) Upper Bound (Round to two decimal places as needed.) (e) What is the difference between the predictions made in parts (a) and (c)? = = O A. The prediction made in part (a) is an estimate of the mean well-being score for all individuals whose commute is 20 minutes, and the prediction made in part (c) is an estimate of the well-being score for the individual, Jane, whose commute is 20 minutes. O B. The prediction made in part (a) is the average well-being score for all individuals whose commute is 68.06 minutes, and the prediction made in part (c) is an estimate of the well-being score for the individual, Jane, whose commute is 68.06 minutes. O C. The prediction made in part (a) is an estimate of the well-being score for the individual, Jane, whose commute is 20 minutes, and the prediction made in part (c) is an estimate of the mean well-being score for all individuals whose commute is 20 minutes.
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