A student was performed on a type of bearing to find the relationship of amount of weary to x₁ = oil viscosity and x2 = load. The accompanying data were obtained. Complete parts (a) and (b) below. Click the icon to view the bearing data. (a) Estimate the unknown parameters of the multiple linear regression equation Hy|x₁.x2 =Bo+B1×1 + B2×2 ŷ= +(1)×₁+()×2 (Round the constant to the nearest integer as needed. Round the x₁-coefficient to two decimal places as needed. Round the x2-coefficient to three decimal places as needed.) Bearing Data y x1 x2 192 1.7 842 173 22.2 1070 112 33.1 1345 233 15.7 805 90 43.2 1209 121 39.8 1125
A student was performed on a type of bearing to find the relationship of amount of weary to x₁ = oil viscosity and x2 = load. The accompanying data were obtained. Complete parts (a) and (b) below. Click the icon to view the bearing data. (a) Estimate the unknown parameters of the multiple linear regression equation Hy|x₁.x2 =Bo+B1×1 + B2×2 ŷ= +(1)×₁+()×2 (Round the constant to the nearest integer as needed. Round the x₁-coefficient to two decimal places as needed. Round the x2-coefficient to three decimal places as needed.) Bearing Data y x1 x2 192 1.7 842 173 22.2 1070 112 33.1 1345 233 15.7 805 90 43.2 1209 121 39.8 1125
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:A student was performed on a type of bearing to find the relationship of amount of weary to x₁ = oil viscosity and
x2 = load. The accompanying data were obtained. Complete parts (a) and (b) below.
Click the icon to view the bearing data.
(a) Estimate the unknown parameters of the multiple linear regression equation Hy|x₁.x2 =Bo+B1×1 + B2×2
ŷ= +(1)×₁+()×2
(Round the constant to the nearest integer as needed. Round the x₁-coefficient to two decimal places as needed.
Round the x2-coefficient to three decimal places as needed.)
Transcribed Image Text:Bearing Data
y
x1
x2
192
1.7
842
173
22.2
1070
112
33.1 1345
233
15.7
805
90
43.2
1209
121
39.8
1125
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