The following data represent a set of 10 experimental runs in which two independent variables X1 and X2 are controlled and values of a response Y are observed: Y 61.5 61.2 32 52.5 31.5 22.5 53 56.8 34.8 52.7 52.53 Estimate the multiple Linear regression, Y = a + b₁ X₁ 1. The regression estimate a. 55.23 1.68 X1 2400 2450 2500 2700 2750 2800 2900 3000 3100 3200 004 X2 54.5 56.4 43.2 65.2 45.5 47.5 65 66.5 57.3 68
The following data represent a set of 10 experimental runs in which two independent variables X1 and X2 are controlled and values of a response Y are observed: Y 61.5 61.2 32 52.5 31.5 22.5 53 56.8 34.8 52.7 52.53 Estimate the multiple Linear regression, Y = a + b₁ X₁ 1. The regression estimate a. 55.23 1.68 X1 2400 2450 2500 2700 2750 2800 2900 3000 3100 3200 004 X2 54.5 56.4 43.2 65.2 45.5 47.5 65 66.5 57.3 68
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
![cements
S
ents
S
Library
For item 1 to 4.
The following data represent a set of 10
experimental runs in which
two independent variables X1 and X2 are controlled and
values of a response Y
are observed:
Y
61.5
61.2
32
52.5
31.5
22.5
53
56.8
34.8
52.7
52.53
Estimate the multiple Linear regression, Y = a + b₁ X₁ + b₂ X₂
1. The regression estimate a.
55.23
1.68
X1
2400
2450
2500
2700
2750
2800
2900
3000
3100
3200
-0.04
X2
54.5
56.4
43.2
65.2
45.5
47.5
65
66.5
57.3
68](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ff37027e2-69db-4cb8-838c-f55b892e26ef%2F5fc12330-ecdd-4704-b144-41b458fcd7aa%2Fsh29hp7_processed.jpeg&w=3840&q=75)
Transcribed Image Text:cements
S
ents
S
Library
For item 1 to 4.
The following data represent a set of 10
experimental runs in which
two independent variables X1 and X2 are controlled and
values of a response Y
are observed:
Y
61.5
61.2
32
52.5
31.5
22.5
53
56.8
34.8
52.7
52.53
Estimate the multiple Linear regression, Y = a + b₁ X₁ + b₂ X₂
1. The regression estimate a.
55.23
1.68
X1
2400
2450
2500
2700
2750
2800
2900
3000
3100
3200
-0.04
X2
54.5
56.4
43.2
65.2
45.5
47.5
65
66.5
57.3
68
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