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  2. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    For B = 10% one requires n = 100, for B = 5% one needs n = 400, for B = 3% the requirement approximates to n = 1000, while for B = 1% a sample size of n = 10000 is required. These numbers are quoted often in news reports of opinion polls and other sample surveys. However, the results reported may not be the exact value as numbers are preferably ...

  3. p-chart - Wikipedia

    en.wikipedia.org/wiki/P-chart

    [2]: 277 If the organization elects to only inspect a fraction of units produced, the sample size should be chosen large enough so that the chance of finding at least one nonconforming unit in a sample is high—otherwise the false alarm rate is too high. One technique is to fix sample size so that there is a 50% chance of detecting a process ...

  4. Stratified sampling - Wikipedia

    en.wikipedia.org/wiki/Stratified_sampling

    Proportionate allocation uses a sampling fraction in each of the strata that are proportional to that of the total population. For instance, if the population consists of n total individuals, m of which are male and f female (and where m + f = n), then the relative size of the two samples (x 1 = m/n males, x 2 = f/n females) should reflect this proportion.

  5. Template:List of statistics symbols - Wikipedia

    en.wikipedia.org/wiki/Template:List_of...

    In general, the subscript 0 indicates a value taken from the null hypothesis, H 0, ... = sample 1 size = sample 2 size ¯ = sample mean ...

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  7. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    A related form are weights normalized to sum to sample size (n). These (non-negative) weights sum to the sample size (n), and their mean is 1. Any set of weights can be normalized to sample size by dividing each weight with the average of all weights.

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  9. Undersampling - Wikipedia

    en.wikipedia.org/wiki/Undersampling

    The darker gray areas correspond to undersampling with the maximum value of n in the equations of this section. In signal processing , undersampling or bandpass sampling is a technique where one samples a bandpass -filtered signal at a sample rate below its Nyquist rate (twice the upper cutoff frequency ), but is still able to reconstruct the ...