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  2. Normal probability plot - Wikipedia

    en.wikipedia.org/wiki/Normal_probability_plot

    Normal probability plots are made of raw data, residuals from model fits, and estimated parameters. A normal probability plot. In a normal probability plot (also called a "normal plot"), the sorted data are plotted vs. values selected to make the resulting image look close to a straight line if the data are approximately normally distributed.

  3. Skewness - Wikipedia

    en.wikipedia.org/wiki/Skewness

    In the older notion of nonparametric skew, defined as () /, where is the mean, is the median, and is the standard deviation, the skewness is defined in terms of this relationship: positive/right nonparametric skew means the mean is greater than (to the right of) the median, while negative/left nonparametric skew means the mean is less than (to ...

  4. Shape of a probability distribution - Wikipedia

    en.wikipedia.org/wiki/Shape_of_a_probability...

    Considerations of the shape of a distribution arise in statistical data analysis, where simple quantitative descriptive statistics and plotting techniques such as histograms can lead on to the selection of a particular family of distributions for modelling purposes. The normal distribution, often called the "bell curve" Exponential distribution

  5. 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 ...

  6. P–P plot - Wikipedia

    en.wikipedia.org/wiki/P–P_plot

    As an example, if the two distributions do not overlap, say F is below G, then the P–P plot will move from left to right along the bottom of the square – as z moves through the support of F, the cdf of F goes from 0 to 1, while the cdf of G stays at 0 – and then moves up the right side of the square – the cdf of F is now 1, as all points of F lie below all points of G, and now the cdf ...

  7. Probability distribution fitting - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution...

    The first two are very similar, while the last, with one degree of freedom, has "heavier tails" meaning that the values farther away from the mean occur relatively more often (i.e. the kurtosis is higher). The Cauchy distribution is also symmetric. Skew distributions to the right. Skewness to left and right

  8. Histogram - Wikipedia

    en.wikipedia.org/wiki/Histogram

    The total area of a histogram used for probability density is always normalized to 1. If the length of the intervals on the x-axis are all 1, then a histogram is identical to a relative frequency plot. Histograms are sometimes confused with bar charts. In a histogram, each bin is for a different range of values, so altogether the histogram ...

  9. L-moment - Wikipedia

    en.wikipedia.org/wiki/L-moment

    There are two common ways that L-moments are used, in both cases analogously to the conventional moments: As summary statistics for data. To derive estimators for the parameters of probability distributions , applying the method of moments to the L-moments rather than conventional moments.