A company wishes to purchase one of five different machines, A, B, C, D, E. The manager conducted the experiment to determine if performance of these machines is different. Test the hypothesis that the performance is different at 0.05 significance. Testing scores are in the table below.
A |
68 |
72 |
77 |
42 |
53 |
B |
72 |
53 |
63 |
53 |
48 |
C |
60 |
82 |
64 |
75 |
72 |
D |
48 |
61 |
57 |
64 |
50 |
E |
64 |
65 |
70 |
68 |
53 |
Hypotheses are:
H0: Performance of these machines is same.
Ha: Performance of these machines is different.
Following is the output of one way ANOVA:
Anova: Single Factor | ||||||
SUMMARY | ||||||
Groups | Count | Sum | Average | Variance | ||
A | 5 | 312 | 62.4 | 210.3 | ||
B | 5 | 289 | 57.8 | 92.7 | ||
C | 5 | 353 | 70.6 | 76.8 | ||
D | 5 | 280 | 56 | 47.5 | ||
E | 5 | 320 | 64 | 43.5 | ||
ANOVA | ||||||
Source of Variation | SS | df | MS | F | P-value | F crit |
Between Groups | 658.16 | 4 | 164.54 | 1.747451147 | 0.17921408 | 2.866081402 |
Within Groups | 1883.2 | 20 | 94.16 | |||
Total | 2541.36 | 24 |
The F test statistics is:
F = 1.747
The p-value is: 0.1792
Since p-value is greater than so we fail to reject the null hypothesis.
That is we cannot conclude that performance of these machines is different.
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