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  2. Z-test - Wikipedia

    en.wikipedia.org/wiki/Z-test

    How to perform a Z test when T is a statistic that is approximately normally distributed under the null hypothesis is as follows: . First, estimate the expected value μ of T under the null hypothesis, and obtain an estimate s of the standard deviation of T.

  3. Standard score - Wikipedia

    en.wikipedia.org/wiki/Standard_score

    Comparison of the various grading methods in a normal distribution, including: standard deviations, cumulative percentages, percentile equivalents, z-scores, T-scores. In statistics, the standard score is the number of standard deviations by which the value of a raw score (i.e., an observed value or data point) is above or below the mean value of what is being observed or measured.

  4. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    The "68–95–99.7 rule" is often used to quickly get a rough probability estimate of something, given its standard deviation, if the population is assumed to be normal. It is also used as a simple test for outliers if the population is assumed normal, and as a normality test if the population is potentially not normal.

  5. Normal curve equivalent - Wikipedia

    en.wikipedia.org/wiki/Normal_curve_equivalent

    50 + 21.063 × z, where z is the standard score or "z-score", i.e. z is how many standard deviations above the mean the raw score is ( z is negative if the raw score is below the mean). The reason for the choice of the number 21.06 is to bring about the following result: If the scores are normally distributed (i.e. they follow the "bell-shaped ...

  6. Standard normal table - Wikipedia

    en.wikipedia.org/wiki/Standard_normal_table

    The standard normal distribution, represented by Z, is the normal distribution having a mean of 0 and a standard deviation of 1. Conversion If X is a random ...

  7. 97.5th percentile point - Wikipedia

    en.wikipedia.org/wiki/97.5th_percentile_point

    In probability and statistics, the 97.5th percentile point of the standard normal distribution is a number commonly used for statistical calculations. The approximate value of this number is 1.96, meaning that 95% of the area under a normal curve lies within approximately 1.96 standard deviations of the mean.

  8. Normality test - Wikipedia

    en.wikipedia.org/wiki/Normality_test

    Simple back-of-the-envelope test takes the sample maximum and minimum and computes their z-score, or more properly t-statistic (number of sample standard deviations that a sample is above or below the sample mean), and compares it to the 68–95–99.7 rule: if one has a 3σ event (properly, a 3s event) and substantially fewer than 300 samples, or a 4s event and substantially fewer than 15,000 ...

  9. Standard deviation - Wikipedia

    en.wikipedia.org/wiki/Standard_deviation

    The mean and the standard deviation of a set of data are descriptive statistics usually reported together. In a certain sense, the standard deviation is a "natural" measure of statistical dispersion if the center of the data is measured about the mean. This is because the standard deviation from the mean is smaller than from any other point.