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  2. 68–95–99.7 rule - Wikipedia

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

    For an approximately normal data set, the values within one standard deviation of the mean account for about 68% of the set; while within two standard deviations account for about 95%; and within three standard deviations account for about 99.7%. Shown percentages are rounded theoretical probabilities intended only to approximate the empirical ...

  3. 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.

  4. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    About 68% of values drawn from a normal distribution are within one standard deviation σ from the mean; about 95% of the values lie within two standard deviations; and about 99.7% are within three standard deviations. [8] This fact is known as the 68–95–99.7 (empirical) rule, or the 3-sigma rule.

  5. Standard deviation - Wikipedia

    en.wikipedia.org/wiki/Standard_deviation

    An estimate of the standard deviation for N > 100 data taken to be approximately normal follows from the heuristic that 95% of the area under the normal curve lies roughly two standard deviations to either side of the mean, so that, with 95% probability the total range of values R represents four standard deviations so that s ≈ R/4.

  6. Histogram - Wikipedia

    en.wikipedia.org/wiki/Histogram

    The data shown is a random sample of 10,000 points from a normal distribution with a mean of 0 and a standard deviation of 1. The data used to construct a histogram are generated via a function m i that counts the number of observations that fall into each of the disjoint categories (known as bins ).

  7. Gaussian function - Wikipedia

    en.wikipedia.org/wiki/Gaussian_function

    The graph of a Gaussian is a characteristic symmetric "bell curve" shape. The parameter a is the height of the curve's peak, b is the position of the center of the peak, and c (the standard deviation, sometimes called the Gaussian RMS width) controls the width of the "bell".

  8. Probability density function - Wikipedia

    en.wikipedia.org/wiki/Probability_density_function

    This probability is given by the integral of this variable's PDF over that range—that is, it is given by the area under the density function but above the horizontal axis and between the lowest and greatest values of the range. The probability density function is nonnegative everywhere, and the area under the entire curve is equal to 1.

  9. Box plot - Wikipedia

    en.wikipedia.org/wiki/Box_plot

    One standard deviation above and below the mean of the data set; The 9th percentile and the 91st percentile of the data set; The 2nd percentile and the 98th percentile of the data set; Rarely, box-plot can be plotted without the whiskers. This can be appropriate for sensitive information to avoid whiskers (and outliers) disclosing actual values ...