Explore: Statistical Samples.

methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population

population (a statistical sample) is chosen to represent the population in a statistical analysis. Moreover, the statistical sample must be unbiased and accurately

Statistical inference is the process of using data analysis to infer properties of an underlying probability distribution. Inferential statistical analysis

or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups

number of samples where each sample, involving multiple observations (data points), is separately used to compute one value of a statistic (for example

statistic (singular) or sample statistic is any quantity computed from values in a sample which is considered for a statistical purpose. Statistical purposes

random samples can be taken one at a time, remembering which samples were taken so far. In two dimensions the difference between random sampling, Latin

the purposes of extracting samples from this population. A "parameter" is to a population as a "statistic" is to a sample; that is to say, a parameter

complicated sampling techniques, such as stratified sampling, the sample can often be split up into sub-samples. Typically, if there are H such sub-samples (from

rejection sampling) that can directly return independent samples from the distribution, and these are free from the problem of autocorrelated samples that