The article “Application of Radial Basis Function Neural Networks in Optimization of Hard Turning of AISID2 Cold –Worked Tool Steel With a Ceramic Tool” (S. Basak, U. Dixit, and J. Davim, Journal of Engineering Manufacture, 2007:987-998) presents the results of an experiment in which tool wear was computed for various values of three factor. We consider two of those factors, cutting speed and cutting time. The results are presented in the following table.
Speed (m/min) |
Time (min) |
Wear (mm) |
|||||
80 |
5 |
5 |
6 |
5 |
5 |
4 |
3 |
80 |
10 |
8 |
8 |
8 |
8 |
8 |
8 |
80 |
15 |
11 |
10 |
9 |
9 |
10 |
9 |
150 |
5 |
9 |
11 |
9 |
8 |
10 |
9 |
150 |
10 |
14 |
14 |
15 |
13 |
17 |
18 |
150 |
15 |
16 |
15 |
26 |
24 |
24 |
25 |
220 |
5 |
34 |
33 |
19 |
21 |
18 |
20 |
220 |
10 |
60 |
59 |
29 |
31 |
28 |
31 |
220 |
15 |
65 |
64 |
31 |
33 |
75 |
80 |
a. Estimate all main effect and interactions.
b.Construct an ANOVA table, You may give ranges for the P-values.
c.Is the additive model plausible? Provide the value of a test statistic and the P-value.
d. can the effect of speed on wear be described by interpreting the main effects of speed? If so, interpret the main effect, including the appropriate test statistic and P-value. If not, explain why not.
e. Can the effect of time on wear be described by interpreting the main effects of time? If so, interpret the main effects, including the appropriate test statistic and P-value. If not, explain why not.
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