I have two samples as follows:

conjps <- c(9.41,10.45,10.78,10.73,11.11,11.12,11.59,11.04,11.63)
ms <- c(4.11,5.10,5.70,6.46,6.04,6.16, 6.24,6.32,7.33)

I want to test if the change of sample is the same to the another one.

conjps_ch <- c(1.04,0.33,...)
ms <- c(0.99,0.60,0.76,...)

Which test I should use, and which conclusion can we drive based on the test?

I used the following test: Test Equality of Two Variances

 F test to compare two variances

data:  conjps and ms

F = 0.5419, num df = 8, denom df = 8, p-value = 0.4045

alternative hypothesis: true ratio of variances is not equal to 1

95 percent confidence interval:

 0.1222368 2.4024170

sample estimates:

ratio of variances


Is it correct? Which conclusion can I get based on this?

  • $\begingroup$ Can you define precisely (in plain English) what a change is in this context? The test you used allows to compare two variances (assuming normality of the parent distributions). $\endgroup$
    – chl
    Oct 30 '12 at 9:45

You may select your answer based on the type of your data and your goal, according to the table below.

It is copied from "Arnaud Delorme, STATISTICAL METHODS, University of San Diego, California, 2005". Please cite this reference if you would like to use the picture in other page.

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