Contents
How do you compare unequal data sets?
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 do you compare mean variances?
How to compare two means when the groups have different standard deviations.
- Conclude that the populations are different.
- Transform your data.
- Ignore the result.
- Go back and rerun the t test, checking the option to do the Welch t test that allows for unequal variance.
- Use a permuation test.
Can I 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 ).
What does unequal variances mean?
For the unequal variance t test, the null hypothesis is that the two population means are the same but the two population variances may differ. The unequal variance t test reports a confidence interval for the difference between two means that is usable even if the standard deviations differ.
Can you perform a one way between subjects Anova If you have unequal sample per group?
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 compare two means?
Comparison of means tests helps you determine if your groups have similar means. There are many cases in statistics where you’ll want to compare means for two populations or samples. The four major ways of comparing means from data that is assumed to be normally distributed are: Independent Samples T-Test.
How to compare two independent population means-unequal?
The test comparing two independent population means with unknown and possibly unequal population standard deviations is called the Aspin-Welch t -test. The degrees of freedom formula we will see later was developed by Aspin-Welch.
How to do two independent sample unequal variance?
Two Independent Samples Unequal Variance (Welch’s Test) To conduct a two independent sample comparison of means test, you follow very similar steps as described in the one sample test with some modifications. For this problem, we want to compare the average weights of blue crabs in two river basins: (1) Tar-Pamlico and (2) Neuse River.
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?
Why is the t test used for unequal sample sizes?
The reason the t test can handle unequal sample sizes is that it takes account of the standard error of the estimates of the means for each group. That is the standard deviation of the group’s distribution divided by the square root of the group’s sample size.