Process of selecting a sample of items from a population
Why using sample instead of census: completeness, cost, time, accuracy
Sampling frame: list of all those within a population who can be sampled
Characteristics: completeness, accuracy, up to date, non-duplication
Random sampling: every item in the population has an equal chance of being included
Drawbacks: unrepresentative sample, scattered population (more spread out rather than focused)
Quasi-random sampling (method of selecting samples combining random and non-random sampling): approximation to random sampling, includes systematic, stratified, and multistage sampling
Systematic: select an element from the list at random and then every kth element
Stratified: divide population into homogeneous subgroups and then sample within each subgroup
Advantages: representative, precise
Disadvantages: not useful when the population cannot be partitioned
Multistage: divide the population into groups and then sample within selected groups
Advantages: cost, speed, convenience
Disadvantages: bias, not truly random
Non-random sampling: used when the sampling frame cannot be established, includes quota and cluster sampling
Quota: segment the population into subgroups and then select subjects from each segment based on a proportion
Advantages: time, budget, accuracy
Disadvantages: unreliable, biased
Cluster: divide the population into groups and then sample all the elements in one or more groups