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  2. 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.

  3. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The uniform distribution or rectangular distribution on [a,b], where all points in a finite interval are equally likely, is a special case of the four-parameter Beta distribution. The Irwin–Hall distribution is the distribution of the sum of n independent random variables, each of which having the uniform distribution on [0,1].

  4. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    Figure 1: The left graph shows a probability density function. The right graph shows the cumulative distribution function. The value at a in the cumulative distribution equals the area under the probability density curve up to the point a. Absolutely continuous probability distributions can be described in several ways.

  5. Student's t-distribution - Wikipedia

    en.wikipedia.org/wiki/Student's_t-distribution

    The resulting UCL will be the greatest average value that will occur for a given confidence interval and population size. In other words, ¯ being the mean of the set of observations, the probability that the mean of the distribution is inferior to UCL 1 − α is equal to the confidence level 1 − α.

  6. Mean - Wikipedia

    en.wikipedia.org/wiki/Mean

    The mean of a set of observations is the arithmetic average of the values; however, for skewed distributions, the mean is not necessarily the same as the middle value (median), or the most likely value (mode). For example, mean income is typically skewed upwards by a small number of people with very large incomes, so that the majority have an ...

  7. Poisson distribution - Wikipedia

    en.wikipedia.org/wiki/Poisson_distribution

    For sufficiently large values of λ, (say λ >1000), the normal distribution with mean λ and variance λ (standard deviation ) is an excellent approximation to the Poisson distribution. If λ is greater than about 10, then the normal distribution is a good approximation if an appropriate continuity correction is performed, i.e., if P( X ≤ x ...

  8. Triangular distribution - Wikipedia

    en.wikipedia.org/wiki/Triangular_distribution

    This distribution for a = 0, b = 1 and c = 0.5—the mode (i.e., the peak) is exactly in the middle of the interval—corresponds to the distribution of the mean of two standard uniform variables, that is, the distribution of X = (X 1 + X 2) / 2, where X 1, X 2 are two independent random variables with standard uniform distribution in [0, 1]. [1]

  9. Random graph - Wikipedia

    en.wikipedia.org/wiki/Random_graph

    Given a random graph of nodes and an average degree . Next we remove randomly a fraction 1 − p {\displaystyle 1-p} of nodes and leave only a fraction p {\displaystyle p} . There exists a critical percolation threshold p c = 1 k {\displaystyle p_{c}={\tfrac {1}{\langle k\rangle }}} below which the network becomes fragmented while above p c ...