Probability distribution of the possible sample outcomes
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 multiple observations (data points), were separately used in order to compute one value of a statistic (such as, for example, the sample mean or sample variance) for each sample, then the sampling distribution is the probability distribution of the values that the statistic takes on. In many contexts, only one sample is observed, but the sampling distribution can be found theoretically.
Sampling distributions are important in statistics because they provide a major simplification en route to statistical inference. More specifically, they allow analytical considerations to be based on the probability distribution of a statistic, rather than on the joint probability distribution of all the individual sample values.
and 21 Related for: Sampling distribution information
In statistics, a samplingdistribution or finite-sampledistribution is the probability distribution of a given random-sample-based statistic. If an arbitrarily...
Gibbs sampling or a Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm for sampling from a specified multivariate probability distribution when...
Importance sampling is a Monte Carlo method for evaluating properties of a particular distribution, while only having samples generated from a different...
standard deviation of its samplingdistribution or an estimate of that standard deviation. If the statistic is the sample mean, it is called the standard...
In statistics, stratified sampling is a method of sampling from a population which can be partitioned into subpopulations. In statistical surveys, when...
Inverse transform sampling (also known as inversion sampling, the inverse probability integral transform, the inverse transformation method, Smirnov transform...
separating the higher half from the lower half of a data sample, a population, or a probability distribution. For a data set, it may be thought of as "the middle"...
distribution function associated with the empirical measure of a sample. This cumulative distribution function is a step function that jumps up by 1/n at each...
distribution, then the sample variance calculated from that infinite set will match the value calculated using the distribution's equation for variance...
occurrences, sampling using a Pólya urn model (in some sense, the "opposite" of sampling without replacement) Categorical distribution, for a single...
computational statistics, rejection sampling is a basic technique used to generate observations from a distribution. It is also commonly called the acceptance-rejection...
random sample : X 1 , X 2 , . . . , X n {\displaystyle X_{1},X_{2},...,X_{n}} . The samplingdistribution is equivalent to the probability distribution of...
hypercube sampling (LHS) is a statistical method for generating a near-random sample of parameter values from a multidimensional distribution. The sampling method...
Pharm Sci 74(2) 229-231 Cox DR (1969) Some sampling problems in technology. In: New developments in survey sampling. U.L. Johnson, H Smith eds. New York: Wiley...
squares showed the samplingdistribution of the statistic is the Cauchy distribution. The Cauchy distribution is often the distribution of observations for...
unimodal distribution (a distribution with a single peak), negative skew commonly indicates that the tail is on the left side of the distribution, and positive...
the sampling is carried out without replacement, the draws are not independent and so the resulting distribution is a hypergeometric distribution, not...
In statistics, cluster sampling is a sampling plan used when mutually homogeneous yet internally heterogeneous groupings are evident in a statistical population...
repeated sampling. That is, the theorem assumes the random sampling produces a samplingdistribution formed from different values of means (or sums) of such...
particular, stratified sampling—dividing the region in sub-domains—and importance sampling—sampling from non-uniform distributions—are two examples of such...
Global Information