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Simple random sample
random selection of persons/units

Systematic Random Sample
Selecting every xth person from a list

Stratified random sample
divide population into similar subgroups, then take a simple random sample from each group

Cluster random sample
divid population into clusters, then randomly sample clusters and measure all units within sampled clusters

Multistage Sample
combo of sampling methods

Convenience/Haphazard sample
Take anyone who is available and wants to volunteer

Quota sampling
selecting people nonrandomly to fulfill a fixed quota (e.g. gender)

Heterogeneity Sampling
Get a diverse range of participants

Snowball Sampling
participants recommend others who are eligable to participate

Random Assignment
Randomly assigning participants to experimental conditions

Random Sampling
Randomly selecting participants from a population to be included in a sample

Sample Size depends on
 Power of statistical technique used
 Research design
 Strength of experimental manipulation > Size of Effect
 Variability of data > experimental control

Errors in Sampling Frame
 Units are not included
 Units are included twice
 Units are included even though they do not belong to population

Systematic Errors
 Error in Sampling Frame
 Measurement errors (e.g. items not understood)
 Missing Responses

