Using the T.TEST Function to Conduct Hypothesis Tests

The T.TEST function provides a quick almost back of the envelope method of testing hypotheses involving two samples. It can be used to test:

Paired samples, sometimes referred to as matched samples or repeated measures

Independent samples, unknown variances but considered equal

Independent samples, unknown and unequal variances

How to Interpret t-test Results

The function returns the probability that the two sample means come from the same population. This probability is more commonly referred to as p-value, and also commonly interpreted from the perspective of the altenative hypothesis. That is the probability that the test results are due to random chance. The p-value can also be defined as the lowest level of significance the null hypothesis can be rejected at, and so it can be directly compared to α to determine whether or not the null hypothesis should be rejected. Finally, p-value can also be defined as the probability of a type I error