1. Sampling
Partially Adapted from The Research Methods Knowledge Base, William Trochim (2006). &
Methods for Social Researchers in Developing Counries, The Ahfad University for Women &
Online Statistics Education: A Multimedia Course of Study, David M. Lane, Rice University.

2. Agenda Introduction Sampling Terminology Types of Sampling
Sampling Biases 2 2

3. Introduction
The purpose of research is to learn something about a larger group – the population
It is often impractical, however, to enumerate an entire population
The alternative is to obtain a representative sample 3 3

4. Sampling Terminology Population: abstract vs target
Sampling element: A single member or unit of target population
Sample frame: list of all sampling elements in target population
Statistic: finding based on a sample; used to estimate a parameter
Parameter: finding based on measuring entire population
Sampling Error/Sampling Bias: how well a statistic estimates a parameter 4 4

5. Types of Sampling Probability Sampling: relies on random selection
Simple random sampling
Stratified random sampling
Systematic random sampling
Cluster sampling
Nonprobability Sampling: no random selection
Convenience Sampling
Quota Sampling
Expert Sampling
Network Sampling 5 5

6. Sampling Biases
Sampling biases are errors that arise due to method of sampling used
There are 3 common types of sampling biases
Self-Selection Bias
Survivorship (Attrition) Bias
Sampling Selection Bias 6 6

7. Self-Selection Bias
People who “self-select” themselves for an experiment might not be representative of the target population
respondents who signup for an online survey about computer use
When people sign-up for an experiment without knowing what it is about and leave subsequently upon finding out
Non-response bias when certain subjects are more likely to respond than others 7 7

8. Survivorship (Attrition) Bias
When observations recorded at the end of an investigation are a non-random set of those present at the beginning of the investigation
Measuring gains in stock funds when poorly performing funds are often eliminated
Measuring effects of school feeding programs when underweight students often drop-out of school 8 8

9. Sampling Selection Bias
Arises through researcher’s choice of sampling method or units sampled
Nonprobability sampling
Under-coverage bias
Researcher samples too few observations from certain segments of the population
U.S Elections Landon-Roosevelt telephone poll: Roosevelt won despite polls in favor of Landon  Poorer people who tend to vote for Roosevelt did not have a telephone 9 9

10. Effects of Biases
Resulting sample becomes less representative of target population
Results of study not as generalizable to the target population 10 10