Abstract
This tutorial gives an overview of sampling techniques commonly used in the field of education such as simple randomized sampling, stratification methods and (multistage) cluster randomized sampling. Advantages and disadvantages of these techniques are described without diving too deep into sampling theory. Instead, each technique is exemplified with data and program code in R. Finally, all presented techniques are combined to show the complexity of samples in famous educational large-scale studies such as PISA. Again an example with R code illustrates the theoretical descriptions.