The t-test is a statistical tool used to determine whether there is a significant difference between the means of two groups. It is commonly used in hypothesis testing when the sample size is small and the population standard deviation is unknown.
1. Independent Samples t-test also called: Two-sample t-test
Purpose: Compares the means of two independent groups.
Assumptions:
- Two groups are unrelated.
- Data is approximately normally distributed.
- Variances are equal (homogeneity of variance).
2. Paired Samples t-test also called: Dependent samples t-test
Purpose: Compares the means of two related groups.
Assumptions:
- Measurements are taken from the same subjects at different times or under different conditions.
- Differences are normally distributed.
3. One Sample t-test
Purpose: Compares the sample mean to a known or hypothesized population mean.
Assumptions:
Data is continuous and approximately normally distributed.
Sample is randomly drawn from the population.
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