An article gave the accompanying data on the dimensions (in cm) of 27 representative food products. Product Maximum Width (cm) Minimum Width (cm) 1 2.55 1.80 2 2.90 2.70 3 2.10 2.00 4 2.90 2.60 5 3.25 3.15 6 2.00 1.80 7 1.55 1.50 8 4.80 3.80 9 5.85 5.00 10 5.80 4.75 11 2.85 2.80 12 2.45 2.10 13 2.55 2.20 14 2.60 2.60 15 2.75 2.60 16 3.10 2.90 17 5.15 5.10 18 10.20 10.20 19 3.45 3.50 20 2.70 1.20 21 3.05 1.70 22 2.70 1.75 23 2.45 1.70 24 2.40 1.20 25 4.45 1.20 26 7.50 7.50 27 4.20 4.25 (a) Fit the simple linear regression model that would allow prediction of the maximum width of a food container based on its minimum width. (Round your answers to three decimal places.) ŷ = _____+(_____)x The data point with the largest residual is for a 1-liter bottle of a certain soft drink. Delete this data point and refit the regression. (Round your answers to three decimal places.) ŷ =_____+(______)x
An article gave the accompanying data on the dimensions (in cm) of 27 representative food products. Product Maximum Width (cm) Minimum Width (cm) 1 2.55 1.80 2 2.90 2.70 3 2.10 2.00 4 2.90 2.60 5 3.25 3.15 6 2.00 1.80 7 1.55 1.50 8 4.80 3.80 9 5.85 5.00 10 5.80 4.75 11 2.85 2.80 12 2.45 2.10 13 2.55 2.20 14 2.60 2.60 15 2.75 2.60 16 3.10 2.90 17 5.15 5.10 18 10.20 10.20 19 3.45 3.50 20 2.70 1.20 21 3.05 1.70 22 2.70 1.75 23 2.45 1.70 24 2.40 1.20 25 4.45 1.20 26 7.50 7.50 27 4.20 4.25 (a) Fit the simple linear regression model that would allow prediction of the maximum width of a food container based on its minimum width. (Round your answers to three decimal places.) ŷ = _____+(_____)x The data point with the largest residual is for a 1-liter bottle of a certain soft drink. Delete this data point and refit the regression. (Round your answers to three decimal places.) ŷ =_____+(______)x
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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15.3 #2
An article gave the accompanying data on the dimensions (in cm) of 27 representative food products.
Product | Maximum Width (cm) | Minimum Width (cm) |
---|---|---|
1 | 2.55 | 1.80 |
2 | 2.90 | 2.70 |
3 | 2.10 | 2.00 |
4 | 2.90 | 2.60 |
5 | 3.25 | 3.15 |
6 | 2.00 | 1.80 |
7 | 1.55 | 1.50 |
8 | 4.80 | 3.80 |
9 | 5.85 | 5.00 |
10 | 5.80 | 4.75 |
11 | 2.85 | 2.80 |
12 | 2.45 | 2.10 |
13 | 2.55 | 2.20 |
14 | 2.60 | 2.60 |
15 | 2.75 | 2.60 |
16 | 3.10 | 2.90 |
17 | 5.15 | 5.10 |
18 | 10.20 | 10.20 |
19 | 3.45 | 3.50 |
20 | 2.70 | 1.20 |
21 | 3.05 | 1.70 |
22 | 2.70 | 1.75 |
23 | 2.45 | 1.70 |
24 | 2.40 | 1.20 |
25 | 4.45 | 1.20 |
26 | 7.50 | 7.50 |
27 | 4.20 | 4.25 |
(a)
Fit the simple linear regression model that would allow prediction of the maximum width of a food container based on its minimum width. (Round your answers to three decimal places.)
ŷ = _____+(_____)x
The data point with the largest residual is for a 1-liter bottle of a certain soft drink. Delete this data point and refit the regression. (Round your answers to three decimal places.)
ŷ =_____+(______)x
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