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.

Agenda Introduction Sampling Terminology Types of Sampling Sampling Biases 2 2

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

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

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

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

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

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

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

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