# Sample size calculation

In the *Sampling* menu, you can calculate the required sample size for some common problems, taking into account the magnitude of differences and the probability to make a correct or a false conclusion.

When you perform a statistical test, you will make a *correct decision* when you

- reject a false null hypothesis, or
- accept a true null hypothesis.

On the other hand you can make *two errors*:

- you can reject a true null hypothesis (
**Type I error**), or - you can accept a false null hypothesis (
**Type II error**).

To calculate the required sample size, you must decide beforehand on:

- the required probability of a Type I error, i.e. the required significance level α (two-sided);
- the required probability of a Type II error, i.e. the required power 1-β of the test;
- a quantification of the study objectives, i.e. decide what difference is biologically or clinically meaningful and worthwhile detecting.

In addition, you will sometimes need to have an idea about expected sample statistics such as e.g. the standard deviation. This can be known from previous studies.