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  2. Simple random sample - Wikipedia

    en.wikipedia.org/wiki/Simple_random_sample

    In statistics, a simple random sample (or SRS) is a subset of individuals (a sample) chosen from a larger set (a population) in which a subset of individuals are chosen randomly, all with the same probability. It is a process of selecting a sample in a random way. In SRS, each subset of k individuals has the same probability of being chosen for ...

  3. Sampling (statistics) - Wikipedia

    en.wikipedia.org/wiki/Sampling_(statistics)

    Sampling (statistics) In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population. The subset is meant to reflect the whole population and statisticians ...

  4. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    In survey methodology, the design effect (generally denoted as , , or ) is a measure of the expected impact of a sampling design on the variance of an estimator for some parameter of a population. It is calculated as the ratio of the variance of an estimator based on a sample from an (often) complex sampling design, to the variance of an ...

  5. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    Sample size determination or estimation 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 the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined ...

  6. Stratified sampling - Wikipedia

    en.wikipedia.org/wiki/Stratified_sampling

    A stratified survey could thus claim to be more representative of the population than a survey of simple random sampling or systematic sampling. Both mean and variance can be corrected for disproportionate sampling costs using stratified sample sizes. Advantages. The reasons to use stratified sampling rather than simple random sampling include

  7. Ratio estimator - Wikipedia

    en.wikipedia.org/wiki/Ratio_estimator

    Under simple random sampling the bias is of the order O( n −1). An upper bound on the relative bias of the estimate is provided by the coefficient of variation (the ratio of the standard deviation to the mean). Under simple random sampling the relative bias is O( n −1/2). Correction of the mean's bias

  8. Sampling distribution - Wikipedia

    en.wikipedia.org/wiki/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 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 ...

  9. Random sample consensus - Wikipedia

    en.wikipedia.org/wiki/Random_sample_consensus

    Random sample consensus ( RANSAC) is an iterative method to estimate parameters of a mathematical model from a set of observed data that contains outliers, when outliers are to be accorded no influence on the values of the estimates. Therefore, it also can be interpreted as an outlier detection method. [1] It is a non-deterministic algorithm in ...