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..