t-test

T-test is a statistical hypothesis test used to determine whether there is a significant difference between the means of two groups of data. It is a common test used in many fields, including medicine, psychology, and social sciences.

The t-test compares the means of two groups and calculates a t-value, which is a measure of the difference between the means of the two groups relative to the variation within the groups. If the t-value is large, it suggests that the difference between the means of the two groups is significant and not due to chance.

The t-test assumes that the data in each group are normally distributed and have equal variances. There are two main types of t-tests: the independent samples t-test, which compares the means of two independent groups, and the paired samples t-test, which compares the means of two related groups (e.g., before and after a treatment).

The results of a t-test are reported as a p-value, which represents the probability of obtaining the observed difference between the means of the two groups by chance alone. If the p-value is less than a predetermined significance level (usually 0.05), the null hypothesis (that there is no significant difference between the means of the two groups) is rejected, and it is concluded that there is a significant difference between the two groups.