# Understanding the results of an F test in R

I am performing the test to see if there is any differences between the preferences of chocolate for male and female students. My null hypothesis is that there is no difference.

My data is not normally distributed and data transformations failed to 'squash' the data. Therefore I performed the F test on the unchanged data:

var.test(dframeA$Chocolate,dframeB$Chocolate)

F test to compare two variances

data:  dframeA$Chocolate and dframeB$Chocolate
F = 0.9539, num df = 238, denom df = 138, p-value = 0.7447
alternative hypothesis: true ratio of variances is not equal to 1
95 percent confidence interval:
0.7041521 1.2768820
sample estimates:
ratio of variances
0.9538888


The above shows the result.

I am very new to R (and statistics for the matter). Please would you help me understand what the results mean? I am assuming that this test is 2-tailed..

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I suggest you now use the side bar the does and "auto-search". –  DWin Dec 8 '13 at 0:00
I am sorry but I am not sure what you mean.. –  user3069564 Dec 8 '13 at 0:13
If you're tying to compare preferences (which seems to suggest some test of location) why are you testing variance? –  Glen_b Dec 8 '13 at 0:28
That is a good question. I guess it is not applicable.. –  user3069564 Dec 8 '13 at 0:29

## migrated from stackoverflow.comDec 7 '13 at 23:35

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