data
1 | 2 | 3 | 4 | |
Calipers | 0.2 | 0.24 | 0.5 | 0.33 |
0.14 | 0.35 | 0.38 | 0.25 | |
0.15 | 0.21 | 0.54 | 0.29 | |
Optimal Comparator | 0.26 | 0.2 | 0.14 | 0.13 |
0.25 | 0.19 | 0.15 | 0.15 | |
0.3 | 0.28 | 0.17 | 0.16 | |
CMM | 0.14 | 0.21 | 0.17 | 0.25 |
0.19 | 0.23 | 0.18 | 0.35 | |
0.17 | 0.24 | 0.21 | 0.27 |
Using Excel
data -> data analysis -> Anova: Two-Factor With Replication
ANOVA | ||||||
Source of Variation | SS | df | MS | F | P-value | F crit |
Instrument | 0.0676 | 2 | 0.0338 | 17.8693 | 0.0000 | 3.4028 |
Technician | 0.0230 | 3 | 0.0077 | 4.0582 | 0.0182 | 3.0088 |
Interaction | 0.1847 | 6 | 0.0308 | 16.2756 | 0.0000 | 2.5082 |
Within | 0.0454 | 24 | 0.0019 | |||
Total | 0.3208 | 35 |
if p-value < alpha, we reject the null hypothesis
here p-value for all effects (instrument, technician and Interaction) are less than alpha (0.05)
hence we reject the null hypothesis
all effects are significant
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