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MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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
Transcribed Image Text:Find the equation of the least-squares regression line for the data found in Table 1.2. Lastly,
are we able to find a line that outputs a smaller total of the sum of the residuals squared
than the least-squares regression line, why or why not?

Transcribed Image Text:# of days running Weight loss (kg)
1
1
3
2
5
6
7
9
7
4
4
5
Metric
# of days mean
# of days
standard deviation
Weight loss mean
Weight loss
standard deviation
T
Result
5
3
4
2
0.62642
Table 1.2: The relationship between running 10km and losing weight in kg.
Expert Solution
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Step 1: Determine the given information
The given paired observations of "days of running" and the "weight loss amount (in kg)" are:
# of days running | Weight loss (kg) |
1 | 1 |
2 | 3 |
5 | 7 |
6 | 4 |
7 | 4 |
9 | 5 |
The summarized data is given as:
Metric | Result |
# of days mean | 5 |
# of days standard deviation | 3 |
Weight loss mean | 4 |
Weight loss standard deviation | 2 |
0.62642 |
The objective is to obtain the regression equation.
Considering the "amount of weight loss" (in kg) (say
Step by stepSolved in 3 steps with 1 images
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