A test statistic is used in a hypothesis test when you are deciding to support or reject the null
hypothesis. The test statistic takes your data from an experiment or survey and compares your results
to the results you would expect from the null hypothesis.
For example, let’s say that you think Drug X will cure genital warts. The currently accepted fact
(the null hypothesis) is that about 30% of warts will go away on their own.
When you run a hypothesis test, you’ll use a distribution like a t-distribution or normal distribution.
These have a known area, and enable to you to calculate a probability value (p-value) that will tell
you if your results are due to chance, or if your results are die to your theory being correct. The larger
the test statistic, the smaller the p-value and the more likely you are to reject the null hypothesis.
