applied maths - sampling

population

whole set of items that are of interest

sample

subset of the population intended to represent the population, cheaper and quicker but data may not be accurate as it may not be large enough to represent small sub-groups

sampling unit

individual thing in a population that can be sampled

sampling frame

list/grouping from which samples are selected

census

the entire population, very accurate but time consuming and expensive

simple random sampling

list members and give each one a unique identifier, use random number generator to select sample and select members that correspond to numbers picked

bias free and easy to carry out but not suitable for large populations and a sample frame is needed

systematic sampling

take every kth element where k=pop size/sample size starting with a random item between one and k

simple and quick to carry out and suitable for large populations but a sampling frame is needed and can introduce bias

stratified sampling

population divided into distinct strata and simple random sampling carried out in each group

reflects population structure, guarantees proportional representation of groups within a population but population must be classified into distinct strata and selection within each stratum suffers same negatives as simple random sampling

quota sampling

population divided into groups according to characteristic, interviewer selects sampling units

quick and easy and allows a small sample to still be representative of a population but non-random sampling can introduce bias and population must be divided into groups

opportunity sampling

sample taken from people who are available at the time of study

easy to carry out and inexpensive but sample unlikely to be representative and highly dependent on individual researcher