# Which test should I use for comparing the change of two samples‏

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

0.5419076


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

• 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). – chl Oct 30 '12 at 9:45