Can you do an 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 ).

How do you do unequal number of samples in one way Anova?

How to Decide to Use a One-Way ANOVA with Unequal Sample Sizes

Create boxplots for each group and see if the spread of values in each group is roughly equal.
Perform a formal statistical test for equal variances like Bartlett’s Test.

How do you compare survey results with different sample sizes?

One way to compare the two different size data sets is to divide the large set into an N number of equal size sets. The comparison can be based on absolute sum of of difference. THis will measure how many sets from the Nset are in close match with the single 4 sample set.

How does unequal sample size affect ANOVA?

Unequal sample sizes can lead to: Unequal variances between samples, which affects the assumption of equal variances in tests like ANOVA. Having both unequal sample sizes and variances dramatically affects statistical power and Type I error rates (Rusticus & Lovato, 2014). A general loss of power.

Can you do one-way ANOVA with unequal sample size?

The main practical issue in one-way ANOVA is that unequal sample sizes affect the robustness of the equal variance assumption. ANOVA is considered robust to moderate departures from this assumption. But that’s not true when the sample sizes are very different.

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 run at test with unequal sample sizes?

If sample sizes in both conditions are equal, the t-test is very robust against unequal variances. If sample sizes are unequal, unequal variances can influence the Type 1 error rate of the t-test by either increasing or decreasing the Type 1 error rate from the nominal (often 0.05) alpha level.

Why can unequal sample sizes be a problem for ANOVA?