Can you do at test with unequal sample sizes?

Even though you can perform a t-test when the sample size is unequal between two groups, it is more efficient to have an equal sample size in two groups to increase the power of the t-test. Welch’s t-test is for unequal variance data.

Can at test compare more than two groups?

Even when more than two groups are compared, some researchers erroneously apply the t test by implementing multiple t tests on multiple pairs of means. For a comparison of more than two group means the one-way analysis of variance (ANOVA) is the appropriate method instead of the t test.

What is the best test to use for comparing the means of the two groups?

t-test
One of the most common tests in statistics, the t-test, is used to determine whether the means of two groups are equal to each other. The assumption for the test is that both groups are sampled from normal distributions with equal variances.

Can you do two way Anova with unequal sample sizes?

If you have unequal variances and equal sample sizes, no problem. The only problem is if you have unequal variances and unequal sample sizes.

Can you use Anova with unequal sample sizes?

You can perform one way ANOVA with unequal sample sizes. You must consider the assumptions of Normality, equality of variance and independence ( that mentioned by Saigopal ) before using ANOVA and in a case of not correct assumption then you must use non-parametric test ( Kruskal-Wallis test ).

Can you do at test with 3 sets of data?

One of the more common statistical tests for three or more data sets is the Analysis of Variance, or ANOVA. To use this test, the data must meet certain criteria. If these assumptions are met, the ANOVA test can be used to analyze the variance of a single dependent variable across three or more samples or data sets.

Which test can be used to compare more than two samples?

Analysis of Variance (ANOVA) for Comparing Multiple Means In order to compare the means of more than two samples coming from different treatment groups that are normally distributed with a common variance, an analysis of variance is often used.

What statistical test to use to compare pre and post tests?

Paired samples t-test– a statistical test of the difference between a set of paired samples, such as pre-and post-test scores. This is sometimes called the dependent samples t-test.

Do sample sizes need to be equal?

You don’t need equal-sized groups to compute accurate statistics. If the sample size imbalance is due to drop-outs rather than due to design, simple randomisation or technical glitches, this is something to take into account when interpreting the results.

Do sample sizes need to be equal for one-way ANOVA?

The short answer: Yes, you can perform a one-way ANOVA when the sample sizes are not equal. Equal sample sizes is not one of the assumptions made in an ANOVA.

Can you do ANOVA with unequal variance?

Let me acquaint you with Welch’s ANOVA. You use it for the same reasons as the classic statistical test, to assess the means of three or more groups. However, Welch’s analysis of variance provides critical benefits and protections because you can use it even when your groups have unequal variances.

Can I use t-test to compare means of two groups?

Originally Answered: Can I use t-test to compare means of two groups with different sizes (100 and 900 people)? Provided that the assumptions of the t-test are met, yes, you can.

Does the t-test assume equal sample sizes?

The t-test does not assume equal sample sizes; however, if the two groups have different variances, then the difference in sample sizes decreases the robustness of the t-test. There are various studies of this, and no complete answer (AFAIK) so, if you do have diferent variances, you might want to use a nonparametric test.

What are the limitations of a t-test?

T-tests that assume equal variances of the two populations aren’t valid when the two populations have different variances, & it’s worse for unequal sample sizes. If the smallest sample size is the one with highest variance the test will have inflated Type I error).

What is the difference between paired t test and independent t test?

If the groups come from a single population (e.g. measuring before and after an experimental treatment), perform a paired t-test. If the groups come from two different populations (e.g. two different species, or people from two separate cities), perform a two-sample t-test (a.k.a. independent t-test).