Normal Distribution: Difference between revisions
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f(''x'') {{=}} (<sup>1</sup>⁄<sub>σ {{math|{{radical|2π}}}}</sub>) ''e''<sup>-<sup>(x-µ) ²</sup>⁄<sub>2σ ²</sub></sup> | f(''x'') {{=}} (<sup>1</sup>⁄<sub>σ {{math|{{radical|2π}}}}</sub>) ''e''<sup>-<sup>(x-µ) ²</sup>⁄<sub>2σ ²</sub></sup> | ||
</big></big> | </big></big> | ||
[[File:Standard Normal Equation.png|thumb|Curve Equation]] | |||
[[File:Standard Normal CDF.png|thumb|CDF]] | |||
[[File:Standard Normal PDF.png|thumb|PDF]] | |||
Revision as of 16:33, 8 August 2013
The normal distribution is
f(x) = (1⁄σ √2π) e-(x-µ) ²⁄2σ ²
- The parameter μ in this formula is the mean or expectation of the distribution (and also its median and mode).
- The parameter σ is its standard deviation; its variance is therefore σ' 2. A random variable with a Gaussian distribution is said to be normally distributed and is called a normal deviate.
