When I do the two tailed t-test using a sample less than 30, can I use this result? This is because I do also still see the t-test table which has degrees of freedom far less than 30. How further small can the sample size be?
1 Answer
T-test are useful if the data is normally distributed and iid (@djima thank you). If the effect size is large you can use the t-test also if the sample size is small. So yes, you can use a t-test with a sample size which is smaller than 30. The effect size can be calculated with Cohen's D.. Under certain circumstances other measures such as the Glass Delta or the Hedges G are more useful.
"The present simulation study showed that there is no fundamental objection to using a regular t-test with extremely small sample sizes. Even a sample size as small as 2 did not pose problems. In most of the simulated cases, the Type I error rate did not exceed the nominal value of 5%. A paired t-test is also feasible with extremely small sample sizes, particularly when the within-pair correlation coefficient is high. (de Winter, 2013, p. 7)
J.C.F. de Winter (2013), "Using the Student’s t-test with extremely small sample sizes," Practical Assessment, Research and Evaluation, 18:10, August, ISSN 1531-7714 http://pareonline.net/getvn.asp?v=18&n=10
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1$\begingroup$ Normally distributed and IID! Correlated samples would inflate t-stats. $\endgroup$– djmaCommented Jul 27, 2017 at 9:26
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$\begingroup$ Thank you. So if the effect size from the Cohen's D test is 2.254386362 while my sample of two groups are 11-14, the t-test is ok, right? $\endgroup$– EricCommented Jul 27, 2017 at 9:28
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$\begingroup$ @Ferdi: then if I have Cohen's D test value of -8.058891649 while each of my two group sample sizes are 9 and 6 respectively, do I conclude that I have enough sample size for t-test? $\endgroup$– EricCommented Jul 27, 2017 at 10:04
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$\begingroup$ Yes. The absolute value of your number is really large. As your sample is very small you can have a look at it "by hand" and it should be evident. $\endgroup$– FerdiCommented Jul 27, 2017 at 10:11
t.test(1,c(3.5,3.2),var.equal=TRUE)
). Details are covered here. $\endgroup$