# 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

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### 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**

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**

### 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.