sampling

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Related to stratified sampling: random sampling, Systematic sampling, Cluster sampling

sampling

the selection of part of a total population of consumers or products whose behaviour or performance can be analysed, in order to make inferences about the behaviour or performance of the total population, without the difficulty and expense of undertaking a complete census of the whole population.

Samples may be chosen randomly, with every consumer or product in the population having an equal chance of being included. Random samples are most commonly used by firms in QUALITY CONTROL where they are used as a basis for selecting products, components or materials for quality testing.

Alternatively, samples may be chosen by dividing up the total population into a number of distinct sub-groups or strata, then selecting a proportionate number of consumers or products from each sub-group since this is quicker and cheaper than random sampling. In MARKETING RESEARCH and opinion polling, quota sampling is usually employed where interviewers select the particular consumers to be interviewed, choosing the numbers of these consumers in proportion to their occurrence in the total population.

Samples may be:

  1. cross-sectional, where sample observations are collected at a particular point in time, for example data on company sales and the incomes of consumers in the current year, embracing a wide range of different income groups, as a basis for investigating the relationship between sales and income;
  2. longitudinal, where sample observations are collected over a number of time periods, for example data on changes in company sales over a number of years and changes in consumer incomes over the same time periods, as a basis for investigating the relationship between sales and income. See STATISTICAL INFERENCES, QUESTIONNAIRE.
References in periodicals archive ?
Usual two-phase ratio and product estimators are defined in stratified sampling respectively as,
Allocation with more than one characteristic in stratified sampling is conflicting in nature, because the best allocation for one characteristic will not, in general, be best for others.
2 * Percentages weighted to Canadian population to account for CCHS multistage stratified sampling strategy Table 2.
In the present paper we apply Dubey and Singh approach to post stratified sampling design.
For highly aggregated populations, an optimized, stratified sampling plan to examine populations is often the most efficient method (Cochran 1963).
Tanne and his associates used stratified sampling to find 8,638 healthy male civil servants and municipal employees aged 40 years or older at baseline, who were participating in the Israeli Ischemic Heart Disease project.
In contrast to a stratified sampling design, poststratification is a method that allocates samples to strata after they have been collected.
A stratified sampling method partitions the collection into clusters or groups, and then accessions within each cluster are selected.
Users can either collect data from all districts, schools and teachers, or use stratified sampling techniques at various levels that would provide a representative sample.
Using a random, stratified sampling procedure, they studied 1,446 members of a Southwest tribe and 1,638 members of two closely related Northern Plains tribes.
Environmentally stratified sampling design for the development of Great Lakes indicators.