Sampling Methods

Front 1

Probability Samples

Back 1

each member of the population has a known non-zero probability of being selected.

Front 2

Random Sampling

Back 2

Each member of the population has an equal and known chance of being selected.

Front 3

Systematic Sampling

Back 3

After the required sample size has been calculated, every Nth record is selected from a list of population members. As long as the list does not contain any hidden order, this sampling method is as good as the random sampling method.

Front 4

Stratified Sampling

Back 4

The researcher first identifies the relevant stratums and their actual representation in the population. Random sampling is then used to select a sufficient number of subjects from each stratum. "Sufficient" refers to a sample size large enough for us to be reasonably confident that the stratum represents the population.

Front 5

Convenience Sampling

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This nonprobability method is often used during preliminary research efforts to get a gross estimate of the results, without incurring the cost or time required to select a random sample.

Front 6

Judgment Sampling

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When using this method, the researcher must be confident that the chosen sample is truly representative of the entire population. a common nonprobability method

Front 7

Quota Sampling

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the nonprobability equivalent of stratified sampling. he researcher first identifies the stratums and their proportions as they are represented in the population. Then convenience or judgment sampling is used to select the required number of subjects from each stratum.

Front 8

Snowball Sampling

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special nonprobability method used when the desired sample characteristic is rare. It may be extremely difficult or cost prohibitive to locate respondents in these situations. relies on referrals from initial subjects to generate additional subjects. While this technique can dramatically lower search costs, it comes at the expense of introducing bias because the technique itself reduces the likelihood that the sample will represent a good cross section from the population.

Front 9

Non-probability samples.

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o not know the probability that each population element will be chosen, and/or we cannot be sure that each population element has a non-zero chance of being chosen.

Front 10

Voluntary sample.

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made up of people who self-select into the survey/study

Front 11

Cluster sampling

Back 11

every member of the population is assigned to one, and only one, group. Each group is called a cluster. A sample of clusters is chosen, using a probability method (often simple random sampling).