Stratified Sampling
Divide population into strata based on shared attributes. Draw random samples from each stratum proportional to its size relative to the population. Ensures final sample represents all subgroups properly.
Simple Random Sampling (SRS)
Assign each member a number. Randomly select samples from the numbered population list until desired sample size is reached. Gives every member equal chance of selection. Allows for unbiased, representative results with measurable random error.
Convenience Sampling
Draw samples from a readily available pool (e.g. students, shoppers). Easy to execute but difficult to defend sample as representative of any larger population beyond the specific pool sampled.
Systematic Sampling
List population in random order. Select every nth case after a random start point. Provides randomly spread out sample while being operationally easier than SRS. Allows for representative sample if start point is well calculated.