Computer Assignment #5
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School
University of North Dakota *
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Course
541
Subject
Industrial Engineering
Date
Dec 6, 2023
Type
docx
Pages
2
Uploaded by MateDonkey3540
Computer assignment
5
Fall 2023
CD
24 points
Write the correct answer in the blanks below and include your output with this page when you turn it in.
Problem 1
A traffic safety officer conducted an experiment to determine whether there is a correlation between people's
ages and driving speeds. Six individuals were randomly sampled and the following data were collected.
Compute a pearson r and then construct a least squares regression equation using age to predict driving speed.
Age
20
25
45
46
60
65
Speed (mph)
60
47
55
38
45
35
(1)
Compute Peason r =
-0.6984
(2) What type of data is needed to compute Pearson r?
Interval or Ratio
(1)
What is the least squares regression equation for using age to predict driving speed.
Y1 = -0.371X +62.792
(1)
What percent of the variance in driving speed can we account for by knowledge of age?
48.7%
(1)What is the slope of the regression line?
-0.371
(1)
What is the Y intercept of the regression line?
62.792
(2)
Is the slope significantly different from 0? (how do you know?)
Yes; -0.371 < 0
(2) For each unit change age what happens to driving speed?
It decreases.
(1)
What number reflects the error in prediction?
51.3% or 7.68645
(1)
What assumption must you satisfy to allow you to correctly interpret the measure of error in prediction?
You must assume that the total percentage of error in the prediction is 100% and that 48.7% is the
measure of precision in the prediction.
1
Problem 2
A researcher collects data on the relationship between the amount of daily exercise an individual gets and the
percent body fat of the individual. The following scores are recorded.
Individual
1
2
3
4
5
Exercise (min)
10
18
26
33
44
% Fat
30
25
18
17
14
Compute a pearson r and then construct a least squares regression equation using exercise in minutes to
predict % body fat..
(1)
Compute Peason r
=
-0.959
(1)
What is the least squares regression equation for using exercise to predict % body fat?
Y1 = -0.476 + 33.272
(1)
What does the least squares regression equation for using exercise to predict % body fat reduce to if
there is no relationship between exercise and %body fat.
X’ = -1.931Y + 66.363
(1)
What percent of the variance in percent body fat can we account for by exercise time in minutes?
47.6%
(1)What is the slope of the regression line?
-0.476
(1)
What is the Y intercept of the regression line?
33.272
(2)
Is the slope significantly different from 0?(how do you know?)
Yes, because the correlation is significant at the 0.01 level
(1)
What number reflects the error in prediction
2.14494
(2)
For each unit change in exercise time
what happens to body fat?
It decreases
2
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