Contents
How many samples do I need for a paired t-test?
two samples
A paired t-test is used to compare two population means where you have two samples in which observations in one sample can be paired with observations in the other sample.
What happens if you perform multiple t tests?
By running two t-tests on the same data you will have increased your chance of “making a mistake” to 10%. The formula for determining the new error rate for multiple t-tests is not as simple as multiplying 5% by the number of tests.
How to calculate Sample Size for t test?
T2_SIZE(d, 1−β, tails, α, nratio, iter, prec) = the minimum sample size required to obtain power of at least 1−β (default .80) in a two sample t test when d = Cohen’s effect size, tails = # of tails: 1 or 2 (default), α = alpha (default = .05) and nratio = the size of the second sample divided by the size of the first sample (default = 1).
How to calculate Sample sizes for two sided tests?
The table below gives sample sizes for a two-sided test of hypothesis that the mean is a given value, with the shift to be detected a multiple of the standard deviation. For a one-sided test at significance level \\(\\alpha\\), look under the value of 2\\(\\alpha\\) in column 1.
Which is larger T2 _ size or T1 _ size?
T2_SIZE (.3) = 176, which is consistent with the fact that a larger sample is required to detect a smaller effect size. Finally, T1_SIZE (.4) = 52, which is consistent with the fact that a paired sample test requires a smaller sample to achieve the same power.
How big of a sample size do you need to detect.4?
Rounding up to the nearest integer, we see that a sample size of 99 is required to detect an effect of .4 with power of about 80%. In fact, we see that a sample size of 99 still leaves us just short of 80% power. We need a sample of size 100 to achieve 80% power; note that T2_POWER (.4,100) = .803648.