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  2. Template:Infobox probability distribution - Wikipedia

    en.wikipedia.org/wiki/Template:Infobox...

    The notation should include all the distribution parameters explained in the next cell. |parameters= — parameters of the distribution family (such as μ and σ 2 for the normal distribution). |support= — the support of the distribution, which may depend on the parameters.

  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. Standard deviation - Wikipedia

    en.wikipedia.org/wiki/Standard_deviation

    If a data distribution is approximately normal then about 68 percent of the data values are within one standard deviation of the mean (mathematically, μ ± σ, where μ is the arithmetic mean), about 95 percent are within two standard deviations (μ ± 2σ), and about 99.7 percent lie within three standard deviations (μ ± 3σ).

  5. Category:Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Category:Normal_distribution

    Skew normal distribution; Skewed generalized t distribution; Slash distribution; Split normal distribution; Standard normal deviate; Standard normal table; Student's t-distribution; Sum of normally distributed random variables

  6. Template:Infobox probability distribution/doc - Wikipedia

    en.wikipedia.org/wiki/Template:Infobox...

    The notation should include all the distribution parameters explained in the next cell. |parameters= — parameters of the distribution family (such as μ and σ 2 for the normal distribution). |support= — the support of the distribution, which may depend on the parameters.

  7. Shape of a probability distribution - Wikipedia

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

    The shape of a distribution will fall somewhere in a continuum where a flat distribution might be considered central and where types of departure from this include: mounded (or unimodal), U-shaped, J-shaped, reverse-J shaped and multi-modal. [1] A bimodal distribution would have two high points rather than one. The shape of a distribution is ...