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Can you use t test for bimodal distribution?
The t–test assumes that the observations within each group are normally distributed. If the distribution is symmetrical, such as a flat or bimodal distribution, the one-sample t–test is not at all sensitive to the non-normality; you will get accurate estimates of the P value, even with small sample sizes.
What is bimodal distribution in statistics?
Statistical Glossary Bimodal literally means “two modes” and is typically used to describe distributions of values that have two centers. For example, the distribution of heights in a sample of adults might have two peaks, one for women and one for men.
How do you know if a data set is unimodal?
Because this data set only has one number that repeats, it is considered a unimodal distribution. Unimodal distribution is when the data set has a single mode. Professor Greenfield’s first class, the one that scored primarily B’s on the math test, would be considered a unimodal distribution.
Which is the best test for bimodal distribution?
Alternatively, you could use the parametric bootstrap cross-fitting method ( pdf ). As mentioned in comments, the Wikipedia page on ‘Bimodal distribution’ lists eight tests for multimodality against unimodality and supplies references for seven of them. There are at least some in R.
Can you teach a class with a bimodal distribution?
Teaching A Class With A Bimodal Distribution — If You Have One! Bimodal distribution with two Gaussian curves superimposed. Generated in Matlab. On his blog Small Pond Science, Terry McGlynn, posed a question “ If you have a bimodal grade distribution, does this change the way you teach the class ?”.
When does a bimodal distribution occur in a graph?
Bimodal distributions can also occur when you’re simply analyzing two different groups of things without realizing it. For example, if you measure the height of plants in a certain field without realizing that two different species are growing in the same field, you’ll see a bimodal distribution when you create a chart.
Which is the best way to test for unimodality?
Only you know what is “reasonable” for your situation, but the following approach might help. For different values of the “cut” between distributions (25%, 30%, 50%, …), compute the mean and standard deviation of the two distributions (above and below the cut).