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Group Statistic Article: easy document editing

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When comparing two groups, you need to decide whether to use a paired test. When comparing three or more groups, the term paired is not apt and the term repeated measures is used instead. Use an unpaired test to compare groups when the individual values are not paired or matched with one another.
A common way to approach that question is by performing a statistical analysis. The two most widely used statistical techniques for comparing two groups, where the measurements of the groups are normally distributed, are the Independent Group t-test and the Paired t-test.
One-way analysis of variance is the typical method for comparing three or more groups means. The usual goal is to determine if at least one group mean (or median) is different from the others. Often follow-up multiple comparison tests are used to determine where the differences occur.
An experimental group (sometimes called a treatment group) is a group that receives a treatment in an experiment. The group is made up of test subjects (people, animals, plants, cells etc.) and the treatment is the variable you are studying. The group that does not receive the treatment is called the control group.
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.
t-test: Comparing Group Means. 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.
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 permutation test.
Two-Sample t-Test. A two-sample t-test is used to test the difference (d0) between two population means. A common application is to determine whether the means are equal.

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