Statistics and Statisticians for Social Sciences
Here are some useful links for getting know literally everything in the arts of hypothesis testing :)
I will just introduce the Two Types of Statistical Errors in two simple pictures:
1. hypothesis testing and statistical errors
A Type I error is often represented by the Greek letter alpha (α) and a Type II error by the Greek letter beta (β). In choosing a level of probability for a test, you are actually deciding how much you want to risk committing a Type I error—rejecting the null hypothesis when it is, in fact, true. For this reason, the area in the region of rejection is sometimes called the alpha level because it represents the likelihood of committing a Type I error.
While we can do nothing with one of the errors, we can easily avoid the other by consciouschoice of a statistical criteria for testing a hypothesis.
For making the right choice, youl just need to be aware of measurement issues (types of scales and levels of measurement).
Having them in mind, please follow these simple guidelines to choose a critetia for testing your hypothesis: