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What is the t-test used for?
A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. The t-test is one of many tests used for the purpose of hypothesis testing in statistics. Calculating a t-test requires three key data values.
Which testing techniques compares two different alternatives?
The Dependent-Samples t Test. The dependent-samples t test (sometimes called the paired-samples t test) is used to compare two means for the same sample tested at two different times or under two different conditions.
When to use a paired or two sample t test?
If you are studying one group, use a paired t-test to compare the group mean over time or after an intervention, or use a one-sample t-test to compare the group mean to a standard value. If you are studying two groups, use a two-sample t-test. If you want to know only whether a difference exists, use a two-tailed test.
Can a t test be used to calculate percentages?
Calculating percentages was just a detour (erroneousely) thinking that the counts could not be used in an analysis. Thomas Hopkins , the issue isn’t that t -test isn’t appropriate for percentages. There are cases where t -test may be (more-or-less) appropriate for percentages.
Can a t test be used for more than two groups?
A t-test should not be used to measure differences among more than two groups, because the error structure for a t-test will underestimate the actual error when many groups are being compared. If you want to compare the means of several groups at once, it’s best to use another statistical test such as ANOVA or a post-hoc test.
What to consider when choosing a t test?
When choosing a t-test, you will need to consider two things: whether the groups being compared come from a single population or two different populations, and whether you want to test the difference in a specific direction. One-sample, two-sample, or paired t-test?