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  2. Sample space - Wikipedia

    en.wikipedia.org/wiki/Sample_space

    A sample space is usually denoted using set notation, and the possible ordered outcomes, or sample points, [5] are listed as elements in the set. It is common to refer to a sample space by the labels S, Ω, or U (for "universal set"). The elements of a sample space may be numbers, words, letters, or symbols.

  3. Latin hypercube sampling - Wikipedia

    en.wikipedia.org/wiki/Latin_hypercube_sampling

    In Latin hypercube sampling one must first decide how many sample points to use and for each sample point remember in which row and column the sample point was taken. Such configuration is similar to having N rooks on a chess board without threatening each other. In orthogonal sampling, the sample space is partitioned into equally probable ...

  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. Probability space - Wikipedia

    en.wikipedia.org/wiki/Probability_space

    This leads to different choices of sample space. The σ-algebra is a collection of all the events we would like to consider. This collection may or may not include each of the elementary events. Here, an "event" is a set of zero or more outcomes; that is, a subset of the sample space. An event is considered to have "happened" during an ...

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  7. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    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 based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power. In complex studies ...

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