In: Math
An engineer is studying the effect of cutting speed on the rate
of metal removal in a machining operation. However, the rate of
metal removal is also related to the hardness of the test specimen.
Five observations are taken at each cutting speed. The amount of
metal removed y and the hardness of the specimen x are shown below
in the format of a data file. Column 1 has treatment (1 for cutting
speed 1000, 2 for cutting speed 1200, 3 for cutting speed 1400),
column 2 has x=hardness, column 3 has y=amount of metal
removed.
1 125 77.4
1 120 68.4
1 140 90.4
1 150 97.9
1 136 87.6
2 133 85.4
2 140 94.4
2 125 74
2 120 64.8
2 165 112.1
3 130 79.6
3 175 117.6
3 132 82.3
3 141 91.9
3 124 72.9
Do an analysis of these data and include the following.
1. A scatterplot of the ys versus the xs, using different symbols
(or colours) to distinguish the points corresponding to different
cutting speeds. Do the ys appear to be related to the xs? Include
regression lines of y versus x for each cutting speed. Does it seem
reasonable to believe that these three lines have the same
slope?
2. An ANCOVA table.
3. An ANOVA table based on the ys, disregarding the xs, to
determine whether there are differences in the (mean) amount of
metal removed for different cutting speeds. Comment on differences
with part (2).
You will be asked a few questions concerning the analysis.
Please use 3 decimal places for the answers below which are not
integer-valued.
Part a)
The type II SS for cutting speed (treatment) is______ and its
degree of freedom is______
Part b)
The MSE for ancova is:______ and its degree
of freedom is______
Part c)
The appropriate F ratio for cutting speed is:
______
Part d)
What is the estimate slope for x=hardness?
______
MINITAB used.
Do an analysis of these data and include the following.
1. A scatterplot of the ys versus the xs, using different symbols
(or colours) to distinguish the points corresponding to different
cutting speeds. Do the ys appear to be related to the xs? Include
regression lines of y versus x for each cutting speed. Does it seem
reasonable to believe that these three lines have the same
slope?
Yes, it appear that y related to the x. It seems reasonable to believe that these three lines have the same slope.
2. An ANCOVA table.
Source |
DF |
Adj SS |
Adj MS |
F-Value |
P-Value |
x |
1 |
2993.47 |
2993.47 |
315.99 |
0.000 |
Group |
2 |
3.90 |
1.95 |
0.21 |
0.817 |
Error |
11 |
104.21 |
9.47 |
||
Total |
14 |
3149.46 |
3. An ANOVA table based on the ys, disregarding the xs, to determine whether there are differences in the (mean) amount of metal removed for different cutting speeds. Comment on differences with part (2).
Analysis of Variance
Source |
DF |
Adj SS |
Adj MS |
F-Value |
P-Value |
Group |
2 |
51.78 |
25.89 |
0.10 |
0.905 |
Error |
12 |
3097.68 |
258.14 |
||
Total |
14 |
3149.46 |
Calculate F=0.10, P=0.905 which is > 0.05 level. Ho is not rejected.
You will be asked a few questions concerning the analysis.
Please use 3 decimal places for the answers below which are not
integer-valued.
Part a)
The type II SS for cutting speed (treatment) is 3.903 and its
degree of freedom is 2
Part b)
The MSE for ancova is: 9.473 and its degree of freedom
is 11
Part c)
The appropriate F ratio for cutting speed is:
0.206
Part d)
What is the estimate slope for x=hardness?
0.9302
MINITAB ouput for ANCOVA
General Linear Model: y versus x, Group
Method
Factor coding |
(-1, 0, +1) |
Factor Information
Factor |
Type |
Levels |
Values |
Group |
Fixed |
3 |
1, 2, 3 |
Analysis of Variance
Source |
DF |
Adj SS |
Adj MS |
F-Value |
P-Value |
x |
1 |
2993.47 |
2993.47 |
315.99 |
0.000 |
Group |
2 |
3.90 |
1.95 |
0.21 |
0.817 |
Error |
11 |
104.21 |
9.47 |
||
Total |
14 |
3149.46 |
Model Summary
S |
R-sq |
R-sq(adj) |
R-sq(pred) |
3.07788 |
96.69% |
95.79% |
93.06% |
Coefficients
Term |
Coef |
SE Coef |
T-Value |
P-Value |
VIF |
Constant |
-41.06 |
7.22 |
-5.69 |
0.000 |
|
x |
0.9302 |
0.0523 |
17.78 |
0.000 |
1.03 |
Group |
|||||
1 |
0.56 |
1.13 |
0.49 |
0.631 |
1.36 |
2 |
0.13 |
1.12 |
0.11 |
0.912 |
1.33 |
Scatterplot of y vs x Group 120 110 100 90 80 70 60 170 180 130 140 150 160 120