1. Chapter 12 Vocabulary

2. Matching: any attempt to force a sample to resemble specified attributed of the population Population Parameter: a numerically valued attribute of a model for the population Statistic, sample statistic: values calculated from sampled data Representative: a sample is “representative” if the statistics computed reflect the population Sampling Frame: a list of individuals from whom the sample is drawn Sampling Variability: natural tendency of randomly drawn samples to differ

3. Types of Sampling Simple Random Sample (SRS): a sample in which each set of elements in the population has an equal chance of selection Stratified Random Sample: population is divided into several subpopulations (strata) and random samples are drawn from each stratum. Each strata is different from each other but the same within the strata.

4. More Types of Sampling Cluster Sample: population is divided into several subpopulations (clusters) and entire clusters are chosen at random. Each cluster is similar to each other and should represent the population Systematic Sample: a sample drawn by selecting individuals systematically from the sample frame

5. Last Types of Sampling Convenience Sample: a sample that consists of conveniently available individuals Multistage Sample: sampling schemes that combine several sampling methods

6. Types of Bias Voluntary Response Bias: when the sample can choose on their own whether to participate in the sample Nonresponse Bias: when a large fraction of those sampled fails to respond Response Bias: anything in the survey design that influences responses

7. Beware Of… non-respondents lengthy surveys influencing responses bias!!!!