# Category: Sampling (statistics)

Stock sampling
Stock sampling is sampling people in a certain state at the time of the survey. This is in contrast to flow sampling, where the relationship of interest deals with duration or survival analysis. In st
Acceptable quality limit
The acceptable quality limit (AQL) is the worst tolerable process average (mean) in percentage or ratio that is still considered acceptable; that is, it is at an acceptable quality level. Closely rela
Expander walk sampling
In the mathematical discipline of graph theory, the expander walk sampling theorem intuitively states that sampling vertices in an expander graph by doing relatively short random walk can simulate sam
Selective recruitment
Selective recruitment is an observed effect in traffic safety. When safety belt laws are passed, belt wearing rates increase, but casualties decline by smaller percentages than estimated in a simple c
Census
A census is the procedure of systematically acquiring, recording and calculating information about the members of a given population. This term is used mostly in connection with national population an
Healthy user bias
The healthy user bias or healthy worker bias is a bias that can damage the validity of epidemiologic studies testing the efficacy of particular therapies or interventions. Specifically, it is a sampli
Scale analysis (statistics)
In statistics, scale analysis is a set of methods to analyze survey data, in which responses to questions are combined to measure a latent variable. These items can be dichotomous (e.g. yes/no, agree/
Effective sample size
No description available.
Stratified sampling
In statistics, stratified sampling is a method of sampling from a population which can be partitioned into subpopulations. In statistical surveys, when subpopulations within an overall population vary
Rock paper scissors
Rock paper scissors (also known by other orderings of the three items, with "rock" sometimes being called "stone," or as Rochambeau, roshambo, or ro-sham-bo) is a hand game originating from China, usu
Balanced repeated replication
Balanced repeated replication is a statistical technique for estimating the sampling variability of a statistic obtained by stratified sampling.
Sufficient similarity
Sufficient similarity is a 20th-century para-legal concept used in the chemical industry for toxicological studies. The term was first employed in a restricted sense to assess surrogacy of chemical mi
Failure bias
Failure bias is the logical error of concentrating on the people or things that failed to make it past some selection process and overlooking those that did, typically because of their lack of visibil
Empirical evidence
Empirical evidence for a proposition is evidence, i.e. what supports or counters this proposition, that is constituted by or accessible to sense experience or experimental procedure. Empirical evidenc
Sampling probability
In statistics, in the theory relating to sampling from finite populations, the sampling probability (also known as inclusion probability) of an element or member of the population, is its probability
Coverage error
Coverage error is a type of non-sampling error that occurs when there is not a one-to-one correspondence between the target population and the sampling frame from which a sample is drawn. This can bia
Acquiescence bias
Acquiescence bias, also known as agreement bias, is a category of response bias common to survey research in which respondents have a tendency to select a positive response option or indicate a positi
Unmatched count
In psychology and social research, unmatched count, or item count, is a technique to improve, through anonymity, the number of true answers to possibly embarrassing or self-incriminating questions. It
Gy's sampling theory
Gy's sampling theory is a theory about the sampling of materials, developed by Pierre Gy from the 1950s to beginning 2000s in articles and books including: * (1960) Sampling nomogram * (1979) Sampli
Civic lottery
A civic lottery, a popular term for the contemporary use of sortition or allotment, is a lottery-based method for selecting citizens for public service or office. It is based on the premise that citiz
Recall bias
In epidemiological research, recall bias is a systematic error caused by differences in the accuracy or completeness of the recollections retrieved ("recalled") by study participants regarding events
Sampling frame
In statistics, a sampling frame is the source material or device from which a sample is drawn. It is a list of all those within a population who can be sampled, and may include individuals, households
Acceptance sampling
Acceptance sampling uses statistical sampling to determine whether to accept or reject a production lot of material. It has been a common quality control technique used in industry. It is usually done
Whipple's index
Whipple's index (or index of concentration), invented by American demographer George Chandler Whipple (1866–1924), is a method to measure the tendency for individuals to inaccurately report their actu
Margin of error
The margin of error is a statistic expressing the amount of random sampling error in the results of a survey. The larger the margin of error, the less confidence one should have that a poll result wou
Heckman correction
The Heckman correction is a statistical technique to correct bias from non-randomly selected samples or otherwise incidentally truncated dependent variables, a pervasive issue in quantitative social s
Sampling bias
In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others. It results in
Stratified randomization
In statistics, stratified randomization is a method of sampling which first stratifies the whole study population into subgroups with same attributes or characteristics, known as strata, then followed
Measuring attractiveness by a categorical-based evaluation technique (MACBETH)
Measuring attractiveness through a categorical-based evaluation technique (MACBETH) is a multiple-criteria decision analysis (MCDA) method that evaluates options against multiple criteria. MACBETH was
Opinion poll
An opinion poll, often simply referred to as a survey or a poll (although strictly a poll is an actual election) is a human research survey of public opinion from a particular sample. Opinion polls ar
Variables sampling plan
In statistics, a variables sampling plan is an acceptance sampling technique. Plans for variables are intended for quality characteristics that are measured on a continuous scale. This plan requires t
Flow sampling
In statistics, in flow sampling, as opposed to stock sampling, observations are collected as they enter the particular state of interest during a particular interval. When dealing with duration data (
Lottery machine
A lottery machine is the machine used to draw the winning numbers for a lottery. Early lotteries were done by drawing numbers, or winning tickets, from a container. In the UK, numbers of winning Premi
Item tree analysis
Item tree analysis (ITA) is a data analytical method which allows constructing ahierarchical structure on the items of a questionnaire or test from observed responsepatterns. Assume that we have a que
Inherent bias
The phrase "inherent bias" refers to the effect of underlying factors or assumptions that skew viewpoints of a subject under discussion. There are multiple formal definitions of "inherent bias" which
Sampling risk
Sampling risk is one of the many types of risks an auditor may face when performing the necessary procedure of audit sampling. Audit sampling exists because of the impractical and costly effects of ex
Survivorship bias
Survivorship bias or survival bias is the logical error of concentrating on entities that passed a selection process while overlooking those that did not. This can lead to incorrect conclusions becaus
Sampling design
In the theory of finite population sampling, a sampling design specifies for every possible sample its probability of being drawn.
Selection bias
Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that proper randomization is not achieved, thereby failing to ensure that the sample o
Coin flipping
Coin flipping, coin tossing, or heads or tails is the practice of throwing a coin in the air and checking which side is showing when it lands, in order to choose between two alternatives, heads or tai
Sample size determination
Sample size determination is the act of choosing the number of observations or replicates to include in a statistical sample. The sample size is an important feature of any empirical study in which th
Sortition
In governance, sortition (also known as selection by lottery, selection by lot, allotment, demarchy, stochocracy, aleatoric democracy, democratic lottery, and lottocracy) is the selection of political
Infrastructure bias
In economics and social policy, infrastructure bias is the influence of the location and availability of pre-existing infrastructure, such as roads and telecommunications facilities, on social and eco
Oversampling and undersampling in data analysis
Within statistics, Oversampling and undersampling in data analysis are techniques used to adjust the class distribution of a data set (i.e. the ratio between the different classes/categories represent
NQuery Sample Size Software
nQuery is a clinical trial design platform used for the design and monitoring of adaptive, group sequential and fixed sample size trials. It is most commonly used by biostatisticians to calculate samp
Imperfect induction
The imperfect induction is the process of inferring from a sample of a group to what is characteristic of the whole group.
Replication (statistics)
In engineering, science, and statistics, replication is the repetition of an experimental condition so that the variability associated with the phenomenon can be estimated. ASTM, in standard E1847, de
Self-selection bias
In statistics, self-selection bias arises in any situation in which individuals select themselves into a group, causing a biased sample with nonprobability sampling. It is commonly used to describe si
Correct sampling
During sampling of granular materials (whether airborne, suspended in liquid, aerosol, or aggregated), correct sampling is defined in Gy's sampling theory as a sampling scenario in which all particles
Sampling error
In statistics, sampling errors are incurred when the statistical characteristics of a population are estimated from a subset, or sample, of that population. Since the sample does not include all membe
Lot quality assurance sampling
Lot quality assurance sampling (LQAS) is a random sampling methodology, originally developed in the 1920s as a method of quality control in industrial production. Compared to similar sampling techniqu
Horvitz–Thompson estimator
In statistics, the Horvitz–Thompson estimator, named after Daniel G. Horvitz and Donovan J. Thompson, is a method for estimating the total and mean of a in a stratified sample. Inverse probability wei
Judgment sample
Judgment sample, or Expert sample, is a type of non-random sample that is selected based on the opinion of an expert. Results obtained from a judgment sample are subject to some degree of bias, due to
Sampling (statistics)
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 o
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.The formula
Prior-independent mechanism
A Prior-independent mechanism (PIM) is a mechanism in which the designer knows that the agents' valuations are drawn from some probability distribution, but does not know the distribution. A typical a
Microdata (statistics)
In the study of survey and census data, microdata is information at the level of individual respondents. For instance, a national census might collect age, home address, educational level, employment
Sampling distribution
In statistics, a sampling distribution or finite-sample distribution is the probability distribution of a given random-sample-based statistic. If an arbitrarily large number of samples, each involving
Horsengoggle
Horsengoggle (also known as horse-and-goggle and horse 'n' goggle and hossengoggle) is a method of selecting a random person from a group. Unlike some other methods, such as rock paper scissors, one o
Strong and weak sampling
Strong and weak sampling are two sampling approach in Statistics, and are popular in computational cognitive science and language learning. In strong sampling, it is assumed that the data are intentio
Multi-attribute global inference of quality
Multi-attribute global inference of quality (MAGIQ) is a multi-criteria decision analysis technique. MAGIQ is based on a hierarchical decomposition of comparison attributes and rating assignment using
Odds and evens (hand game)
Odds and evens is a simple game of chance and hand game, involving two people simultaneously revealing a number of fingers and winning or losing depending on whether they are odd or even, or alternati
Drawing straws
Drawing straws is a selection method, or a form of sortition, that is used by a group to choose one member of the group to perform a task after none has volunteered for it. The same practice can be us
Statistical unit
In statistics, a unit is one member of a set of entities being studied. It is the main source for the mathematical abstraction of a "random variable". Common examples of a unit would be a single perso
Cohen's h
In statistics, Cohen's h, popularized by Jacob Cohen, is a measure of distance between two proportions or probabilities. Cohen's h has several related uses: * It can be used to describe the differenc
Kleroterion
A kleroterion (Ancient Greek: κληρωτήριον) was a randomization device used by the Athenian polis during the period of democracy to select citizens to the boule, to most state offices, to the nomotheta
Statistical benchmarking
In statistics, benchmarking is a method of using auxiliary information to adjust the sampling weights used in an estimation process, in order to yield more accurate estimates of totals. Suppose we hav