Sampling (statistics)

samplingrandom samplesamplestatistical samplingsampling theoryrepresentative samplerandom samplingsampledrandom allocationrandomized
In statistics, quality assurance, and survey methodology, sampling is the selection of a subset (a statistical sample) of individuals from within a statistical population to estimate characteristics of the whole population.wikipedia
447 Related Articles

Statistics

statisticalstatistical analysisstatistician
In statistics, quality assurance, and survey methodology, sampling is the selection of a subset (a statistical sample) of individuals from within a statistical population to estimate characteristics of the whole population.
When a census is not feasible, a chosen subset of the population called a sample is studied.

Acceptance sampling

quality control
Acceptance sampling is used to determine if a production lot of material meets the governing specifications.
Acceptance sampling uses statistical sampling to determine whether to accept or reject a production lot of material.

Survey sampling

surveyssampleSample Survey
In survey sampling, weights can be applied to the data to adjust for the sample design, particularly in stratified sampling.
The purpose of sampling is to reduce the cost and/or the amount of work that it would take to survey the entire target population.

Quality assurance

QAquality assessmentquality
In statistics, quality assurance, and survey methodology, sampling is the selection of a subset (a statistical sample) of individuals from within a statistical population to estimate characteristics of the whole population.
Along with a team at AT&T that included Harold Dodge and Harry Romig, he worked to put sampling inspection on a rational statistical basis as well.

Sample (statistics)

samplesamplesstatistical sample
In statistics, quality assurance, and survey methodology, sampling is the selection of a subset (a statistical sample) of individuals from within a statistical population to estimate characteristics of the whole population.
The best way to avoid a biased or unrepresentative sample is to select a random sample, also known as a probability sample.

Opinion poll

opinion pollingpollapproval rating
For example, in an opinion poll, possible sampling frames include an electoral register and a telephone directory.
An opinion poll, often simply referred to as a poll or a survey, is a human research survey of public opinion from a particular sample.

Survey methodology

surveysurveysstatistical survey
In statistics, quality assurance, and survey methodology, sampling is the selection of a subset (a statistical sample) of individuals from within a statistical population to estimate characteristics of the whole population.
That target population can range from the general population of a given country to specific groups of people within that country, to a membership list of a professional organization, or list of students enrolled in a school system (see also sampling (statistics) and survey sampling).

Sampling frame

frame errorgridsample frame
As a remedy, we seek a sampling frame which has the property that we can identify every single element and include any in our sample.
In statistics, a sampling frame is the source material or device from which a sample is drawn.

Stratified sampling

stratificationstratifiedstratified random sampling
In survey sampling, weights can be applied to the data to adjust for the sample design, particularly in stratified sampling.
In statistics, stratified sampling is a method of sampling from a population which can be partitioned into subpopulations.

Cluster sampling

clustercluster random samplescluster sample
Cluster sampling is commonly implemented as multistage sampling.
Cluster sampling is a sampling plan used when mutually homogeneous yet internally heterogeneous groupings are evident in a statistical population.

Selection bias

selection effectselectionbias
These conditions give rise to exclusion bias, placing limits on how much information a sample can provide about the population.
Sampling bias is systematic error due to a non-random sample of a population, causing some members of the population to be less likely to be included than others, resulting in a biased sample, defined as a statistical sample of a population (or non-human factors) in which all participants are not equally balanced or objectively represented.

Nonprobability sampling

purposive samplingnon-probability samplingjudgmental sampling
Nonprobability sampling methods include convenience sampling, quota sampling and purposive sampling.
Sampling is the use of a subset of the population to represent the whole population or to inform about (social) processes that are meaningful beyond the particular cases, individuals or sites studied.

Sampling bias

ascertainment biasbiased samplebias
The model is then built on this biased sample.
If this is not accounted for, results can be erroneously attributed to the phenomenon under study rather than to the method of sampling.

Sampling fraction

The ratio of the size of this random selection (or sample) to the size of the population is called a sampling fraction.
In sampling theory, the sampling fraction is the ratio of sample size to population size or, in the context of stratified sampling, the ratio of the sample size to the size of the stratum.

Randomization

randomizedrandomizingrandomisation
As long as the starting point is randomized, systematic sampling is a type of probability sampling.
As both selecting random samples and random permutations can be reduced to simply selecting random numbers, random number generation methods are now most commonly used, both hardware random number generators and pseudo-random number generators.

Quota sampling

quota methodquota sampleQuota Samples
Nonprobability sampling methods include convenience sampling, quota sampling and purposive sampling.
In quota sampling, there is non-random sample selection and this can be unreliable.

Poisson sampling

Poisson trial
In a simple PPS design, these selection probabilities can then be used as the basis for Poisson sampling.
In the theory of finite population sampling, Poisson sampling is a sampling process where each element of the population is subjected to an independent Bernoulli trial which determines whether the element becomes part of the sample.

Statistical population

populationsubpopulationsubpopulations
In statistics, quality assurance, and survey methodology, sampling is the selection of a subset (a statistical sample) of individuals from within a statistical population to estimate characteristics of the whole population.

Sampling error

sampling variabilitysampling variationless reliable
The likely size of the sampling error can generally be controlled by taking a large enough random sample from the population, although the cost of doing this may be prohibitive; see sample size determination and statistical power for more detail.

W. Edwards Deming

DemingEdwards DemingWilliam Edwards Deming
Educated initially as an electrical engineer and later specializing in mathematical physics, he helped develop the sampling techniques still used by the U.S. Department of the Census and the Bureau of Labor Statistics.

Snowball sampling

snowballingRespondent Driven Samplingrespondent-driven sampling
In social science research, snowball sampling is a similar technique, where existing study subjects are used to recruit more subjects into the sample.

Confidence interval

confidence intervalsconfidence levelconfidence
These were not expressed as modern confidence intervals but as the sample size that would be needed to achieve a particular upper bound on the sampling error with probability 1000/1001.
Let X be a random sample from a probability distribution with statistical parameters θ, which is a quantity to be estimated, and φ, representing quantities that are not of immediate interest.

Line-intercept sampling

line transectdung countline transect method
Line-intercept sampling is a method of sampling elements in a region whereby an element is sampled if a chosen line segment, called a "transect", intersects the element.
* Sampling (statistics)

Observation

observerobservationsobserved
Each observation measures one or more properties (such as weight, location, colour) of observable bodies distinguished as independent objects or individuals.

Probability theory

theory of probabilityprobabilityprobability theorist
Results from probability theory and statistical theory are employed to guide the practice.