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?
Big Ideas Math A Bridge To Success Algebra 1: Student Edition 2015
1st Edition
ISBN:9781680331141
Author:HOUGHTON MIFFLIN HARCOURT
Publisher:HOUGHTON MIFFLIN HARCOURT
Chapter4: Writing Linear Equations
Section: Chapter Questions
Problem 11CT
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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?](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F572b2a65-dc80-44a4-b9de-5b61af19373f%2F52b0a6e8-d885-4c8b-aa0b-d6d62de9fbad%2Feby27ks_processed.jpeg&w=3840&q=75)
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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