•Chapter 4:Designing Studies...

Sampling

Convenience Sample

Voluntary Response Sample

Simple Random Sample

Stratified Random Sample

Cluster Sample

Types of Samples

Stratified Random Samplepopulation is divided into groups of similar individuals (strata), then an SRS is chosen within each stratause when there’s reason to suggest different subsets would give different resultscapitalizes on pockets of homogeneity within populationserves to decrease variability in results from different samples

Cluster Samplepopulation divided into groups (clusters) whose characteristics mirror those of the population, an SRS of the clusters is chosen, and all individuals within chosen clusters are includedcapitalizes on heterogeneity in populationgenerally does NOT serve to decrease variability, but often is more convenient to use

Why random samples?helps reduce bias in samplingallows us to infer information about the population from what we know about the samplevariability from sample to sample is NOT haphazard...follows laws of probability

How big a sample should we use?

depends....more specifics latergenerally larger samples give better info about population than smaller samples

Errors in Surveys

Sampling ErrorNonsampling Error

Sampling Erroruse of poor sampling methodsundercoverage - when some groups in a population are left out of the sampling process

Nonsampling Errornonresponse error - when individual chosen for sample can’t be contacted or refuses to participateresponse bias - when individual surveyed gives incorrect responsewording and order of questions can also influence the response given