What is T-Test?

T-Test meaning originates from the realm of statistics. T-Test is defined as a method used to compare the means of two groups, which may be related or unrelated, in order to determine the probability of difference between the two data sets.

T-Test is also a form of hypothesis testing, where data samples are used to test an assumption. 

The test uses three crucial values:

• the difference between the two means of the two groups; 

• the standard deviation of each group under consideration; and

• the number of data sets of each group.

A T-Test also takes into account the t-statistic and t-distribution values – a type of probability distribution – and the degrees of freedom to calculate the statistical measure. 

T-Test explained

The T-Test allows analysts to weigh the average values of two data sets. The average values can be used to find out if the data sets belong to the same population or group. 

The T-Test formula should only be conducted where one needs to compare the means of two data sets. Where the number of data sets is more than two, it is not advised to use the test.

There are different types of T-Tests, including a One-Sample T-Test, a Two-Sample T-Test, a Paired T-Test, an Equal Variance T-Test and an Unequal Variance T-Test. Each test has their own use. 

Let us consider the simplest of the types mentioned above, the One-Sample T-Test, and what different T-Test types are used for. 

In this method, the mean of a given data set is compared with the set average. The set average may be the theoretical value or the mean value of the group. The T-Test calculation is as follows:

The One-Sample T-Test is used to determine the mean or average of one population to weigh it against the set average.

The Two-Sample T-Test is used when the samples belong to two different data sets or groups.

The Paired T-Test is a type of hypothesis testing used when two data sets have been derived from the same group.

The Equal Variance T-Test is used when the size of the sample in each group is identical, or the two data sets have a similar variance.

The Unequal Variance T-Test is used when both the number of samples in each group and variance are different.