A student was performed on a type of bearing to find the relationship of amount of wear y 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 μylx1,x2 = Po +B1x1 + B2x2 y= 359 + (-1.18)x+(-0.164) ×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.) (b) Predict wear when oil viscosity is 20 and load is 1000. ŷ = ☐ (Round 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 wear y 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 μylx1,x2 = Po +B1x1 + B2x2 y= 359 + (-1.18)x+(-0.164) ×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.) (b) Predict wear when oil viscosity is 20 and load is 1000. ŷ = ☐ (Round 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
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter3: Functions And Graphs
Section3.3: Lines
Problem 76E
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