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Correlation and Prediction Problems Below are commute times and amounts of rainfall for a few randomly selected days last year. Rain (mm) Commute time (min) 20 10 25 IT 15 12 Treat "Rain" as the X variable. 30 60 25 1) [5 pts.] Draw a scatterplot of the above data. 2) [5 pts.] Compute the value of the r statistic for the correlation between amount of rain and commute time. 3) [5 pts.] Determine the least squares prediction equation for the above data. 4) [2 pt.] Using the regression equation computed above, draw the regression line on the scatterplot from Problem #1. 5) [1 pts.] On average, how long should the commute last when there are 14 mm of rain? 6) [5 pt.] Compute the standard error of the prediction. What does that statistic tell you?

Correlation and Prediction Problems Below are commute times and amounts of rainfall for a few randomly selected days last year. Rain (mm) Commute time (min) 20 10 25 IT 15 12 Treat "Rain" as the X variable. 30 60 25 1) [5 pts.] Draw a scatterplot of the above data. 2) [5 pts.] Compute the value of the r statistic for the correlation between amount of rain and commute time. 3) [5 pts.] Determine the least squares prediction equation for the above data. 4) [2 pt.] Using the regression equation computed above, draw the regression line on the scatterplot from Problem #1. 5) [1 pts.] On average, how long should the commute last when there are 14 mm of rain? 6) [5 pt.] Compute the standard error of the prediction. What does that statistic tell you?

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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Correlation and Prediction Problems Below are commute times and amounts of rainfall for a few randomly selected days last year. Rain (mm) Commute time (min) 20 10 25 IT 15 12 Treat "Rain" as the X variable. 30 60 25 1) [5 pts.] Draw a scatterplot of the above data. 2) [5 pts.] Compute the value of the r statistic for the correlation between amount of rain and commute time. 3) [5 pts.] Determine the least squares prediction equation for the above data. 4) [2 pt.] Using the regression equation computed above, draw the regression line on the scatterplot from Problem #1. 5) [1 pts.] On average, how long should the commute last when there are 14 mm of rain? 6) [5 pt.] Compute the standard error of the prediction. What does that statistic tell you?
Transcribed Image Text:Correlation and Prediction Problems Below are commute times and amounts of rainfall for a few randomly selected days last year. Rain (mm) Commute time (min) 20 10 25 IT 15 12 Treat "Rain" as the X variable. 30 60 25 1) [5 pts.] Draw a scatterplot of the above data. 2) [5 pts.] Compute the value of the r statistic for the correlation between amount of rain and commute time. 3) [5 pts.] Determine the least squares prediction equation for the above data. 4) [2 pt.] Using the regression equation computed above, draw the regression line on the scatterplot from Problem #1. 5) [1 pts.] On average, how long should the commute last when there are 14 mm of rain? 6) [5 pt.] Compute the standard error of the prediction. What does that statistic tell you?
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