1
Chapter 7– Solutions
7.1
Consider the experiment described in Problem 6.1. Analyze this experiment assuming that each
replicate represents a block of a single production shift.
Source of
Sum of
Degrees of
Mean
Variation
Squares
Freedom
Square
F
0
Cutting Speed (
A
)
0.67
1
0.67
<1
Tool Geometry (
B
)
770.67
1
770.67
22.38*
Cutting Angle (
C
)
280.17
1
280.17
8.14*
AB
16.67
1
16.67
<1
AC
468.17
1
468.17
13.60*
BC
48.17
1
48.17
1.40
ABC
28.17
1
28.17
<1
Blocks
0.58
2
0.29
Error
482.08
14
34.43
Total
2095.33
23
Design Expert Output
Response:
Life
in hours
ANOVA for Selected Factorial Model
Analysis of variance table [Partial sum of squares]
Sum of
Mean
F
Source
Squares
DF
Square
Value
Prob > F
Block
0.58
2
0.29
Model
1519.67
4
379.92
11.23
0.0001
significant
A
0.67
1
0.67
0.020
0.8900
B
770.67
1
770.67
22.78
0.0002
C
280.17
1
280.17
8.28
0.0104
AC
468.17
1
468.17
13.84
0.0017
Residual
575.08
17
33.83
Cor Total
2095.33
23
The Model Fvalue of 11.23 implies the model is significant.
There is only
a 0.01% chance that a "Model FValue" this large could occur due to noise.
Values of "Prob > F" less than 0.0500 indicate model terms are significant.
In this case B, C, AC are significant model terms.
These results agree with the results from Problem 6.1.
Tool geometry, cutting angle and the interaction
between cutting speed and cutting angle are significant at the 5% level.
The model also includes factor
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 Fall '03
 StefanSteiner
 Normal Distribution, Source Squares DF, Squares DF Square, Expert Output Response, DF Square Block

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