Sample (statistics)

samplesamplesstatistical samplesampleddata samplenpopulationsample sizesamplingsample data
In statistics and quantitative research methodology, a data sample is a set of data collected and the world selected from a statistical population by a defined procedure.wikipedia
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Statistics

statisticalstatistical analysisstatistician
In statistics and quantitative research methodology, a data sample is a set of data collected and the world selected from a statistical population by a defined procedure.
When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey samples.

Statistic

sample statisticempiricalmeasure
Samples are collected and statistics are calculated from the samples, so that one can make inferences or extrapolations from the sample to the population.
A statistic (singular) or sample statistic is any quantity computed from values in a sample, often the mean.

Statistical population

populationsubpopulationsubpopulations
In statistics and quantitative research methodology, a data sample is a set of data collected and the world selected from a statistical population by a defined procedure. The data sample may be drawn from a population without replacement (i.e. no element can be selected more than once in the same sample), in which case it is a subset of a population; or with replacement (i.e. an element may appear multiple times in the one sample), in which case it is a multisubset.
In statistical inference, a subset of the population (a statistical sample) is chosen to represent the population in a statistical analysis.

Simple random sample

random samplingsimple random samplingsampling without replacement
Several types of random samples are simple random samples, systematic samples, stratified random samples, and cluster random samples.
In statistics, a simple random sample is a subset of individuals (a sample) chosen from a larger set (a population).

Data set

datasetdatasetsdata sets
In statistics and quantitative research methodology, a data sample is a set of data collected and the world selected from a statistical population by a defined procedure.

Convenience sampling

convenience sampleAccidental samplingConvenience Samples
Some examples of nonrandom samples are convenience samples, judgment samples, purposive samples, quota samples, snowball samples, and quadrature nodes in quasi-Monte Carlo methods.
Convenience sampling (also known as grab sampling, accidental sampling, or opportunity sampling) is a type of non-probability sampling that involves the sample being drawn from that part of the population that is close to hand.

Judgment sample

Some examples of nonrandom samples are convenience samples, judgment samples, purposive samples, quota samples, snowball samples, and quadrature nodes in quasi-Monte Carlo methods.
Judgment sample, or Expert sample, is a type of random sample that is selected based on the opinion of an expert.

Estimation theory

parameter estimationestimationestimated
The first is a statistical sample – a set of data points taken from a random vector (RV) of size N.

Independent and identically distributed random variables

independent and identically distributedi.i.d.iid
In mathematical terms, given a probability distribution F, a random sample of length n (where n may be any positive integer) is a set of realizations of n independent, identically distributed (iid) random variables with distribution F.
In statistics, it is commonly assumed that observations in a sample are effectively i.i.d.. The assumption (or requirement) that observations be i.i.d. tends to simplify the underlying mathematics of many statistical methods (see mathematical statistics and statistical theory).

Sample size determination

sample sizeSampling sizessample
Sample size determination is the act of choosing the number of observations or replicates to include in a statistical sample.

Probability distribution

distributioncontinuous probability distributiondiscrete probability distribution
In mathematical terms, given a probability distribution F, a random sample of length n (where n may be any positive integer) is a set of realizations of n independent, identically distributed (iid) random variables with distribution F.
When a sample (a set of observations) is drawn from a larger population, the sample points have an empirical distribution that is discrete and that provides information about the population distribution.

Sampling (statistics)

samplingrandom samplesample
The best way to avoid a biased or unrepresentative sample is to select a random sample, also known as a probability 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.

Quantitative research

quantitativequantitative methodsquantitative data
In statistics and quantitative research methodology, a data sample is a set of data collected and the world selected from a statistical population by a defined procedure.

Statistical unit

experimental unitunitsexperimental units
The elements of a sample are known as sample points, sampling units or observations.

Census

UK censuscensusespopulation census
Typically, the population is very large, making a census or a complete enumeration of all the values in the population either impractical or impossible.

Enumeration

enumeratedenumerativelist
Typically, the population is very large, making a census or a complete enumeration of all the values in the population either impractical or impossible.

Inference

inferredinferlogical inference
Samples are collected and statistics are calculated from the samples, so that one can make inferences or extrapolations from the sample to the population.

Extrapolation

extrapolateextrapolatedextrapolating
Samples are collected and statistics are calculated from the samples, so that one can make inferences or extrapolations from the sample to the population.

Subset

supersetproper subsetsubsets
The data sample may be drawn from a population without replacement (i.e. no element can be selected more than once in the same sample), in which case it is a subset of a population; or with replacement (i.e. an element may appear multiple times in the one sample), in which case it is a multisubset.

Systematic sampling

systematic methodsystematic random samplingsystematic samples
Several types of random samples are simple random samples, systematic samples, stratified random samples, and cluster random samples.

Stratified sampling

stratificationstratifiedstratified random sampling
Several types of random samples are simple random samples, systematic samples, stratified random samples, and cluster random samples.

Cluster sampling

clustercluster random samplescluster sample
Several types of random samples are simple random samples, systematic samples, stratified random samples, and cluster random samples.

Sampling bias

ascertainment biasbiased samplebias
A sample that is not random is called a non-random sample or a non-probability sampling.

Nonprobability sampling

purposive samplingnon-probability samplingjudgmental sampling
Some examples of nonrandom samples are convenience samples, judgment samples, purposive samples, quota samples, snowball samples, and quadrature nodes in quasi-Monte Carlo methods. A sample that is not random is called a non-random sample or a non-probability sampling.

Quota sampling

quota methodquota sampleQuota Samples
Some examples of nonrandom samples are convenience samples, judgment samples, purposive samples, quota samples, snowball samples, and quadrature nodes in quasi-Monte Carlo methods.