The following three waves contain angular data in radians.
data1 | data2 | data3 |
0.807147 | 0.805069 | 0.868458 |
0.833586 | 0.864931 | 0.908372 |
0.82321 | 0.798963 | 0.882047 |
0.852588 | 0.737689 | 0.826652 |
0.803217 | 0.836012 | 0.871351 |
0.801726 | 0.825248 | 0.838512 |
0.802302 | 0.858259 | 0.862167 |
0.685651 | 0.734124 | 0.816303 |
0.856109 | 0.749409 | 0.871654 |
0.84199 | 0.765344 | 0.999934 |
0.784985 | 0.739025 | 0.855328 |
0.845909 | 0.799217 | 0.912431 |
Testing the hypothesis H0: data1 and data2 are samples from the same distribution. To run the test execute:
StatsWatsonUSquaredTest/T=1/Q data1,data2
The results are displayed in the Watson U2 Test table:
Total_Points | 24 |
Watson_U2 | 0.1386 |
Critical_Tiku | 0.18524 |
Approx_P | 0.130043 |
Critical | 0.186238 |
In this case the U2 statistic is smaller than the critical value and so H0: (the two samples came from the same distribution) can't be rejected. Note that although we don't really need the Tiku approximation in this case, it appears to be pretty close to the exact critical value.
Applying the same test to data1 and data3:
StatsWatsonUSquaredTest/T=1/Q data1,data3
The results are displayed in the Watson U2 Test table:
Total_Points | 24 |
Watson_U2 | 0.20370 |
Critical_Tiku | 0.18524 |
Approx_P | 0.03405 |
Critical | 0.18623 |
The test statistic is larger than the critical value so we reject H0 (at the 0.05 significance).
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