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Bearing Data y X1 X2 193 1.7 845 175 22.1 1055 112 32.9 1345 235 15.3 822 92 42.7 1199 120 40.1 1116 - X A study 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) The model y; = Po + ß1×1; +ß2×2; + ß12×1¡×2; +&;, for i = 1, 2, ..., 6 may be considered to describe the data. The X1X2 is an "interaction" term. Fit this model and estimate the parameters. ŷ= 110 + (8.896) ×₁ + (0.115) ×₂ + ( − 0.01038)×1×2 (Round the constant to the nearest integer as needed. Round the x₁X2-coefficient to five decimal places as needed. Round all other coefficients to three decimal places as needed.) (b) Use the models (x1). (×1,x2), (X2). (×1.×2.X1×2) and compute PRESS, Cp, and s² to determine the "best" model. Compute PRESS for each model. Model х1 X1,X2 PRESS (Round to one decimal place as needed.) X1 X2 X1 X2

Bearing Data y X1 X2 193 1.7 845 175 22.1 1055 112 32.9 1345 235 15.3 822 92 42.7 1199 120 40.1 1116 - X A study 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) The model y; = Po + ß1×1; +ß2×2; + ß12×1¡×2; +&;, for i = 1, 2, ..., 6 may be considered to describe the data. The X1X2 is an "interaction" term. Fit this model and estimate the parameters. ŷ= 110 + (8.896) ×₁ + (0.115) ×₂ + ( − 0.01038)×1×2 (Round the constant to the nearest integer as needed. Round the x₁X2-coefficient to five decimal places as needed. Round all other coefficients to three decimal places as needed.) (b) Use the models (x1). (×1,x2), (X2). (×1.×2.X1×2) and compute PRESS, Cp, and s² to determine the "best" model. Compute PRESS for each model. Model х1 X1,X2 PRESS (Round to one decimal place as needed.) X1 X2 X1 X2

Advanced Engineering Mathematics
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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I need help with part b attached images and data. Please make sure to Round to one decimal place as​ needed.

Bearing Data y X1 X2 193 1.7 845 175 22.1 1055 112 32.9 1345 235 15.3 822 92 42.7 1199 120 40.1 1116 - X
Transcribed Image Text:Bearing Data y X1 X2 193 1.7 845 175 22.1 1055 112 32.9 1345 235 15.3 822 92 42.7 1199 120 40.1 1116 - X
A study 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) The model y; = Po + ß1×1; +ß2×2; + ß12×1¡×2; +&;, for i = 1, 2, ..., 6 may be considered to describe the data. The X1X2 is an "interaction" term. Fit this model and estimate the parameters. ŷ= 110 + (8.896) ×₁ + (0.115) ×₂ + ( − 0.01038)×1×2 (Round the constant to the nearest integer as needed. Round the x₁X2-coefficient to five decimal places as needed. Round all other coefficients to three decimal places as needed.) (b) Use the models (x1). (×1,x2), (X2). (×1.×2.X1×2) and compute PRESS, Cp, and s² to determine the "best" model. Compute PRESS for each model. Model х1 X1,X2 PRESS (Round to one decimal place as needed.) X1 X2 X1 X2
Transcribed Image Text:A study 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) The model y; = Po + ß1×1; +ß2×2; + ß12×1¡×2; +&;, for i = 1, 2, ..., 6 may be considered to describe the data. The X1X2 is an "interaction" term. Fit this model and estimate the parameters. ŷ= 110 + (8.896) ×₁ + (0.115) ×₂ + ( − 0.01038)×1×2 (Round the constant to the nearest integer as needed. Round the x₁X2-coefficient to five decimal places as needed. Round all other coefficients to three decimal places as needed.) (b) Use the models (x1). (×1,x2), (X2). (×1.×2.X1×2) and compute PRESS, Cp, and s² to determine the "best" model. Compute PRESS for each model. Model х1 X1,X2 PRESS (Round to one decimal place as needed.) X1 X2 X1 X2
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