The t-test is a widely used statistical test that helps determine if there is a significant difference between the means of two groups. It is particularly useful when the sample sizes are small and the population standard deviation is unknown. The t-test can be categorized into three main types: one-sample t-test, independent two-sample t-test, and paired sample t-test.

In a one-sample t-test, you compare the sample mean to a known value (e.g., population mean). The independent two-sample t-test compares the means of two independent groups, while the paired sample t-test is used when the samples are related or matched in some way. Each type of t-test has its own formula for calculating the t-statistic, which is essential for determining the p-value and making decisions about the null hypothesis ²⁵.

Understanding the assumptions and conditions for using the t-test is crucial for accurate results. These include normality of the data, homogeneity of variances, and the scale of measurement.