Contents
Can you compare percentages with at test?
No. You would do a Chi-squared test to compare two frequency distributions. Your data are the absolute frequencies (counts) – not the percentages! The Chi-squared test considers that the uncertainty is larger when the counts are smaller.
How do I calculate a percentage increase between two percentages?
First: work out the difference (increase) between the two numbers you are comparing. Then: divide the increase by the original number and multiply the answer by 100. % increase = Increase ÷ Original Number × 100. If your answer is a negative number, then this is a percentage decrease.
How can I compare groups with unequal sample sizes?
One group is n=4 and the other is n=68. The n=4 group doesn’t have enough subjects to really test for normality so I’m not sure if a t-test for independent means will work. I’m thinking probably a Mann-Whitney U test. Any suggestions? Is it even possible to compare the means between the two groups with such a difference in size?
Are there unequal sample sizes for mixed ANOVA?
However, all these different groups have different numbers of examinees. The first group has 490 participants, the second group has 1919 participants and the third group has 529 participants. Thus, I can say that I have unequal sample sizes for Mixed ANOVA.
What’s the difference between 500 and 4 samples?
However both of them are of highly different sizes, i.e one has 500 samples while the other has 4. I want to determine if the differences between the samples is statistically significant. I thought of using an unpaired t-test, but I am not sure if the difference in sample sizes would invalidate the method.
Do you need to undersample to make sample sizes equal?
So this undersampling to make the sample sizes equal seems to corroborate the idea that the number of days between targeting and engagement for these two groups is, in fact, different. The answer to your bolded question is no. (And you don’t need to upsample or downsample anything.)