A study 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) The model y₁ = ẞ0 + ẞ1×11 + ẞ2×2i+ẞ12x11x2i+, 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) x2 + ( − 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), (X1,X2,X1×2) and compute PRESS, Cp, and s² to determine the "best" model. Compute PRESS for each model. Model PRESS x1 x1,x2 A x2 X1 X2 X1 X2 (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

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
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A study 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) The model y₁ = ẞ0 + ẞ1×11 + ẞ2×2i+ẞ12x11x2i+, 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) x2 + ( − 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), (X1,X2,X1×2) and compute PRESS, Cp, and s² to determine the "best" model.
Compute PRESS for each model.
Model
PRESS
x1
x1,x2
A
x2
X1 X2 X1 X2
(Round to one decimal place as needed.)
Transcribed Image Text:A study 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) The model y₁ = ẞ0 + ẞ1×11 + ẞ2×2i+ẞ12x11x2i+, 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) x2 + ( − 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), (X1,X2,X1×2) and compute PRESS, Cp, and s² to determine the "best" model. Compute PRESS for each model. Model PRESS x1 x1,x2 A x2 X1 X2 X1 X2 (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
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
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