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  2. Z-test - Wikipedia

    en.wikipedia.org/wiki/Z-test

    Difference between Z-test and t-test: Z-test is used when sample size is large (n>50), or the population variance is known. t-test is used when sample size is small (n<50) and population variance is unknown. There is no universal constant at which the sample size is generally considered large enough to justify use of the plug-in test.

  3. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]

  4. Test statistic - Wikipedia

    en.wikipedia.org/wiki/Test_statistic

    (z is the distance from the mean in relation to the standard deviation of the mean). For non-normal distributions it is possible to calculate a minimum proportion of a population that falls within k standard deviations for any k (see: Chebyshev's inequality). Two-sample z-test

  5. Paired difference test - Wikipedia

    en.wikipedia.org/wiki/Paired_difference_test

    If we only consider the means, the paired and unpaired approaches give the same result. To see this, let Y i1, Y i2 be the observed data for the i th pair, and let D i = Y i2 − Y i1. Also let D, Y 1, and Y 2 denote, respectively, the sample means of the D i, the Y i1, and the Y i2. By rearranging terms we can see that

  6. Chauvenet's criterion - Wikipedia

    en.wikipedia.org/wiki/Chauvenet's_criterion

    The idea behind Chauvenet's criterion finds a probability band that reasonably contains all n samples of a data set, centred on the mean of a normal distribution.By doing this, any data point from the n samples that lies outside this probability band can be considered an outlier, removed from the data set, and a new mean and standard deviation based on the remaining values and new sample size ...

  7. Standard score - Wikipedia

    en.wikipedia.org/wiki/Standard_score

    In educational assessment, T-score is a standard score Z shifted and scaled to have a mean of 50 and a standard deviation of 10. [ 14 ] [ 15 ] [ 16 ] In bone density measurements, the T-score is the standard score of the measurement compared to the population of healthy 30-year-old adults, and has the usual mean of 0 and standard deviation of 1.

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    mail.aol.com

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  9. Standard normal table - Wikipedia

    en.wikipedia.org/wiki/Standard_normal_table

    Z tables use at least three different conventions: . Cumulative from mean gives a probability that a statistic is between 0 (mean) and Z.Example: Prob(0 ≤ Z ≤ 0.69) = 0.2549.

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