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Chapter 4: Designing Studies... Sampling. Convenience Sample Voluntary Response Sample Simple Random Sample Stratified Random Sample Cluster Sample Convenience.

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Presentation on theme: "Chapter 4: Designing Studies... Sampling. Convenience Sample Voluntary Response Sample Simple Random Sample Stratified Random Sample Cluster Sample Convenience."— Presentation transcript:

1 Chapter 4: Designing Studies... Sampling

2 Convenience Sample Voluntary Response Sample Simple Random Sample Stratified Random Sample Cluster Sample Convenience Sample Voluntary Response Sample Simple Random Sample Stratified Random Sample Cluster Sample Types of Samples

3 Stratified Random Sample population is divided into groups of similar individuals (strata), then an SRS is chosen within each strata use when there’s reason to suggest different subsets would give different results capitalizes on pockets of homogeneity within population serves to decrease variability in results from different samples population is divided into groups of similar individuals (strata), then an SRS is chosen within each strata use when there’s reason to suggest different subsets would give different results capitalizes on pockets of homogeneity within population serves to decrease variability in results from different samples

4 Cluster Sample population 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 included capitalizes on heterogeneity in population generally does NOT serve to decrease variability, but often is more convenient to use population 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 included capitalizes on heterogeneity in population generally does NOT serve to decrease variability, but often is more convenient to use

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

6 How big a sample should we use? depends....more specifics later generally larger samples give better info about population than smaller samples depends....more specifics later generally larger samples give better info about population than smaller samples

7 Errors in Surveys Sampling Error Nonsampling Error Sampling Error Nonsampling Error

8 Sampling Error use of poor sampling methods undercoverage - when some groups in a population are left out of the sampling process use of poor sampling methods undercoverage - when some groups in a population are left out of the sampling process

9 Nonsampling Error nonresponse error - when individual chosen for sample can’t be contacted or refuses to participate response bias - when individual surveyed gives incorrect response wording and order of questions can also influence the response given nonresponse error - when individual chosen for sample can’t be contacted or refuses to participate response bias - when individual surveyed gives incorrect response wording and order of questions can also influence the response given


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