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  2. Shapiro–Wilk test - Wikipedia

    en.wikipedia.org/wiki/Shapiro–Wilk_test

    The Shapiro–Wilk test tests the null hypothesis that a sample x1, ..., xn came from a normally distributed population. The test statistic is. where. with parentheses enclosing the subscript index i is the i th order statistic, i.e., the i th-smallest number in the sample (not to be confused with ). is the sample mean.

  3. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The simplest case of a normal distribution is known as the standard normal distribution or unit normal distribution. This is a special case when μ = 0 {\textstyle \mu =0} and σ 2 = 1 {\textstyle \sigma ^{2}=1} , and it is described by this probability density function (or density): φ ( z ) = e − z 2 2 2 π . {\displaystyle \varphi (z ...

  4. Truncated normal distribution - Wikipedia

    en.wikipedia.org/wiki/Truncated_normal_distribution

    CDF. Mean. Median. Mode. Variance. Entropy. MGF. In probability and statistics, the truncated normal distribution is the probability distribution derived from that of a normally distributed random variable by bounding the random variable from either below or above (or both).

  5. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    Then, the distribution of the random variable. is called the log-normal distribution with parameters and . These are the expected value (or mean) and standard deviation of the variable's natural logarithm, not the expectation and standard deviation of itself. Relation between normal and log-normal distribution.

  6. Shapiro–Francia test - Wikipedia

    en.wikipedia.org/wiki/Shapiro–Francia_test

    Let : be the mean of the th order statistic when making independent draws from a normal distribution. For example, m 2 : 4 ≈ − 0.297 {\displaystyle m_{2:4}\approx -0.297} , meaning that the second-lowest value in a sample of four draws from a normal distribution is typically about 0.297 standard deviations below the mean. [ 2 ]

  7. Multivariate normal distribution - Wikipedia

    en.wikipedia.org/wiki/Multivariate_normal...

    The multivariate normal distribution is said to be "non-degenerate" when the symmetric covariance matrix is positive definite. In this case the distribution has density [5] where is a real k -dimensional column vector and is the determinant of , also known as the generalized variance.

  8. Skew normal distribution - Wikipedia

    en.wikipedia.org/wiki/Skew_normal_distribution

    The exponentially modified normal distribution is another 3-parameter distribution that is a generalization of the normal distribution to skewed cases. The skew normal still has a normal-like tail in the direction of the skew, with a shorter tail in the other direction; that is, its density is asymptotically proportional to for some positive .

  9. Normality test - Wikipedia

    en.wikipedia.org/wiki/Normality_test

    A graphical tool for assessing normality is the normal probability plot, a quantile-quantile plot (QQ plot) of the standardized data against the standard normal distribution. Here the correlation between the sample data and normal quantiles (a measure of the goodness of fit) measures how well the data are modeled by a normal distribution. For ...