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Bata Below represent commute times (in minutes) and scores on a well-being survey. Complete parts (a) through (d) below. mute Time (minutes), x -Being Index Score, y 5 15 30 35 60 72 105 - 69.0 67.7 66.1 65.7 63.5 63.2 59.6 Find the least-squares regression line treating the commute time, x, as the explanatory variable and the index score, y, as the response variable. -0.089 x+(69.086) ound to three decimal places as needed.) ) Interpret the slope and y-intercept, if appropriate. rst interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. A. For every unit increase in index score, the commute time falls by .090, on average. (Round to three decimal places as needed.) OB. For a commute time of zero inutes, the index score is predicted to be (Round to three decimal places as needed.) OC. For an index score of zero, the commute time is predicted to be (Round to three decimal places as needed.) OD. For every unit increase in commute time, the index score falls by (Round to three decimal places as needed.) OE. It is not appropriate to interpret the slope. minutes. on average. A

Bata Below represent commute times (in minutes) and scores on a well-being survey. Complete parts (a) through (d) below. mute Time (minutes), x -Being Index Score, y 5 15 30 35 60 72 105 - 69.0 67.7 66.1 65.7 63.5 63.2 59.6 Find the least-squares regression line treating the commute time, x, as the explanatory variable and the index score, y, as the response variable. -0.089 x+(69.086) ound to three decimal places as needed.) ) Interpret the slope and y-intercept, if appropriate. rst interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. A. For every unit increase in index score, the commute time falls by .090, on average. (Round to three decimal places as needed.) OB. For a commute time of zero inutes, the index score is predicted to be (Round to three decimal places as needed.) OC. For an index score of zero, the commute time is predicted to be (Round to three decimal places as needed.) OD. For every unit increase in commute time, the index score falls by (Round to three decimal places as needed.) OE. It is not appropriate to interpret the slope. minutes. on average. A

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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### Understanding the Relationship Between Commute Time and Well-Being Score The data below represent commute times (in minutes) and scores on a well-being survey. | Commute Time (minutes), x | 5 | 15 | 30 | 35 | 60 | 72 | 105 | |---------------------------|-----|-----|-----|-----|-----|-----|-----| | Well-Being Index Score, y | 69.0 | 67.7 | 66.1 | 65.7 | 63.5 | 63.2 | 59.6 | Using this data, we find the least-squares regression line treating the commute time, \( x \), as the explanatory variable and the index score, \( y \), as the response variable: \[ y = -0.089x + (69.06) \] #### Steps to Interpret the Regression Equation: 1. **Slope Interpretation:** - The slope of the regression line is -0.089. This means that for every unit increase in commute time (in minutes), the well-being index score decreases by 0.089 units, on average. - **Correct Choice:** - **A.** For every unit increase in index score, the commute time falls by 0.090, on average. - **Note:** This interpretation is reversed; it needs to be corrected as: For every unit increase in commute time, the index score falls by 0.089, on average. - **B.** For a commute time of zero minutes, the index score is predicted to be [fill-in required]. - **C.** For an index score of zero, the commute time is predicted to be [fill-in required]. - **D.** For every unit increase in commute time, the index score falls by [fill-in required], on average. - **E.** It is not appropriate to interpret the slope. 2. **Y-Intercept Interpretation:** - The y-intercept of the regression line is 69.06. This indicates that when the commute time is zero (i.e., if someone has no commute time), the predicted well-being index score would be 69.06. - **Correct Choice:** - **B.** For a commute time of zero minutes, the index score is predicted to be **69.06
Transcribed Image Text:### Understanding the Relationship Between Commute Time and Well-Being Score The data below represent commute times (in minutes) and scores on a well-being survey. | Commute Time (minutes), x | 5 | 15 | 30 | 35 | 60 | 72 | 105 | |---------------------------|-----|-----|-----|-----|-----|-----|-----| | Well-Being Index Score, y | 69.0 | 67.7 | 66.1 | 65.7 | 63.5 | 63.2 | 59.6 | Using this data, we find the least-squares regression line treating the commute time, \( x \), as the explanatory variable and the index score, \( y \), as the response variable: \[ y = -0.089x + (69.06) \] #### Steps to Interpret the Regression Equation: 1. **Slope Interpretation:** - The slope of the regression line is -0.089. This means that for every unit increase in commute time (in minutes), the well-being index score decreases by 0.089 units, on average. - **Correct Choice:** - **A.** For every unit increase in index score, the commute time falls by 0.090, on average. - **Note:** This interpretation is reversed; it needs to be corrected as: For every unit increase in commute time, the index score falls by 0.089, on average. - **B.** For a commute time of zero minutes, the index score is predicted to be [fill-in required]. - **C.** For an index score of zero, the commute time is predicted to be [fill-in required]. - **D.** For every unit increase in commute time, the index score falls by [fill-in required], on average. - **E.** It is not appropriate to interpret the slope. 2. **Y-Intercept Interpretation:** - The y-intercept of the regression line is 69.06. This indicates that when the commute time is zero (i.e., if someone has no commute time), the predicted well-being index score would be 69.06. - **Correct Choice:** - **B.** For a commute time of zero minutes, the index score is predicted to be **69.06
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