# Sampling

Sampling is at the very core of statistical tests: drawing conclusions on research populations based on (small) samples from those populations. Basically **all statistical tests** quietly assume that the data you're analyzing are a simple random sample from your population. This assumption being ignored is the very reason why political polls are often widely off and research findings can't be replicated.

The tutorials below explain what sampling is and how to draw random samples from your data in SPSS. Mastering this skill greatly facilitates running simulation studies like we presented when explaining ANOVA and the chi-square independence test.

# SPSS Sampling Tutorials

## Draw a Stratified Random Sample

*“I have 5 groups of 10 cases in my data. How can I draw a stratified random sample from these cases? That is, from groups 1 through 5 I'd like to draw exactly 5, 4, 5, 6 and 3 cases at random. What's an efficient way to do this?”* Read More

## SPSS Sampling Basics

How to draw one or many samples from your data in SPSS? This tutorial demonstrates some simple ways for doing so. We'll point out some tips, tricks and pitfalls along the way. Read More

# Sampling Theory

## Simple Random Sampling – What Is It?

Popular statistical procedures such as ANOVA, a chi-square test or a t-test quietly rely on the assumption that your data are a simple random sample from your population. This tutorial walks you through simple random sampling in normal language. Read More

## Survey Sampling – How Does It Work?

Survey Sampling: short introduction to main steps and concepts such as the target population, sampling frame and non response. Read More