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  2. 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.

  3. Partial least squares path modeling - Wikipedia

    en.wikipedia.org/wiki/Partial_least_squares_path...

    A recent study suggests that this claim is generally unjustified, and proposes two methods for minimum sample size estimation in PLS-PM. [ 13 ] [ 14 ] Another point of contention is the ad hoc way in which PLS-PM has been developed and the lack of analytic proofs to support its main feature: the sampling distribution of PLS-PM weights.

  4. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    For example, let the design effect, for estimating the population mean based on some sampling design, be 2. If the sample size is 1,000, then the effective sample size will be 500. It means that the variance of the weighted mean based on 1,000 samples will be the same as that of a simple mean based on 500 samples obtained using a simple random ...

  5. Completely randomized design - Wikipedia

    en.wikipedia.org/wiki/Completely_randomized_design

    In the design of experiments, completely randomized designs are for studying the effects of one primary factor without the need to take other nuisance variables into account. This article describes completely randomized designs that have one primary factor.

  6. Ratio estimator - Wikipedia

    en.wikipedia.org/wiki/Ratio_estimator

    where n is the size of the sample and the r i are estimated with the omission of one pair of variates at a time. [10] An alternative method is to divide the sample into g groups each of size p with n = pg. [11] Let r i be the estimate of the i th group. Then the estimator

  7. Asymptotic theory (statistics) - Wikipedia

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

    In statistics, asymptotic theory, or large sample theory, is a framework for assessing properties of estimators and statistical tests. Within this framework, it is often assumed that the sample size n may grow indefinitely; the properties of estimators and tests are then evaluated under the limit of n → ∞. In practice, a limit evaluation is ...

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  9. Probability-proportional-to-size sampling - Wikipedia

    en.wikipedia.org/wiki/Probability-proportional...

    The pps sampling results in a fixed sample size n (as opposed to Poisson sampling which is similar but results in a random sample size with expectancy of n). When selecting items with replacement the selection procedure is to just draw one item at a time (like getting n draws from a multinomial distribution with N elements, each with their own ...