§2.3: Sampling Methods

Sampling data collection that involves the selection of an unbiased or random subset of individual observations

Sampling Process Determine the population Select a sampling method Determine the sample size Sample and collect data

Sampling Methods Random Sampling sampling in which selections are made without prejudice or bias Non-random Sampling sampling in which selections are made with prejudice and/or bias

Simple Random Sampling Every member of the population has equal probability of being selected Putting names in a hat and blindly choosing Sometimes just referred to as random sampling

Systematic Random Sampling requires a list of the population this list should not be sorted or even partially sorted to any criteria pick every nth item/person on the list n should be between 1 and pop/sampsize

Stratified Sampling stratified related to the word “stratum” meaning layer break up the population into categories (males & females, age strata) proportionally sample each strata relative to its representation in the population

Cluster Sampling sometimes called block sampling population should be divided into groups that are heterogeneous and representative of the population a sufficient number of groups are selected to meet the sample size requirement

Multi-Stage Sampling basically two part sampling using sampling methods we already know Cluster sampling Simple random sampling This is why cluster sampling must have groups that are already representative of the population

Snowball Sampling start out with a partial sample of the population ask all members of that sample to suggest or invite others to be a part of the sample group continue until you reach your sample size useful for groups of people who aren’t accounted for easily (eg. homeless individuals)

Homework Pg 99 #1, 3