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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. Variables sampling plan - Wikipedia

    en.wikipedia.org/wiki/Variables_sampling_plan

    This plan requires the knowledge of the statistical model (e.g. normal distribution). The historical evolution of this technique dates back to the seminal work of W. Allen Wallis (1943). The purpose of a plan for variables is to assess whether the process is operating far enough from the specification limit.

  4. PS Power and Sample Size - Wikipedia

    en.wikipedia.org/wiki/PS_Power_and_Sample_Size

    Matched or independent study designs may be used. Power, sample size, and the detectable alternative hypothesis are interrelated. The user specifies any two of these three quantities and the program derives the third. A description of each calculation, written in English, is generated and may be copied into the user's documents.

  5. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    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 sample.

  6. Power (statistics) - Wikipedia

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

    According to this formula, the power increases with the values of the effect size and the sample size n, and reduces with increasing variability . In the trivial case of zero effect size, power is at a minimum ( infimum ) and equal to the significance level of the test α , {\displaystyle \alpha \,,} in this example 0.05.

  7. Theoretical sampling - Wikipedia

    en.wikipedia.org/wiki/Theoretical_sampling

    3. Changing the size of your sample during the course of the research The first two features of a theoretical sample deals with issues right at the beginning of the research project. The third feature however deals with concerns or application during the process of the research.

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

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

    [4]: 250 So, for example, if we have 3 clusters with 10, 20 and 30 units each, then the chance of selecting the first cluster will be 1/6, the second would be 1/3, and the third cluster will be 1/2. 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 ...

  9. Blocking (statistics) - Wikipedia

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

    In the first example provided above, the sex of the patient would be a nuisance variable. For example, consider if the drug was a diet pill and the researchers wanted to test the effect of the diet pills on weight loss. The explanatory variable is the diet pill and the response variable is the amount of weight loss.