Survey Sampling Tutorial
Saavy statisticians use probability samples when they conduct survey research. Probability sampling makes it possible for researchers to estimate the extent to which
sample estimates reflect
true population parameters.
About the Tutorial
This tutorial covers the essence of probabilty sampling clearly and simply in just a few short lessons. The
tutorial focuses on five topics:
- Prerequisites. To use probability sampling effectively, it helps to know about non-probability samples and survey bias.
- Data collection. We look at three methods for collecting probability samples: simple random sampling,
stratified sampling, and cluster sampling.
- Analysis. It is not enough to collect data in the right way. You also need to analyze it correctly. We show how to analyze
data from simple random samples, stratified samples, and cluster samples.
- Sample planning. How to compare different data collection methods to find the optimum design (most precision, least cost).
- Hypothesis testing. Traditionally, researchers analyze survey data to estimate population parameters. But the same techniques
can be used to test hypotheses.
This tutorial is designed for students and researchers who have some familiarity with introductory statistics (e.g., a high school statistics course or
Advanced Placement Statistics).
How to Use This Tutorial
Individual lessons are accessible through the table of contents, which can be
found in the vertical column on the left side of the page. You should work through lessons
in the order in which they appear; because some lessons build on
previous lessons.
Individual lessons are accessible through the table of contents, which can be
accessed by tapping the "Survey Sampling: Table of Contents" button at the top of the page. You should work through lessons
in the order in which they appear; because some lessons build on
previous lessons.
