Normal Distribution: Difference between revisions

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f(''x'') {{=}} (<sup>1</sup>&frasl;<sub>σ {{math|{{radical|2π}}}}</sub>) ''e''<sup>-<sup>(x-µ)&thinsp;&sup2;</sup>&frasl;<sub>2&sigma;&thinsp;&sup2;</sub></sup>
f(''x'') {{=}} (<sup>1</sup>&frasl;<sub>σ {{math|{{radical|2π}}}}</sub>) ''e''<sup>-<sup>(x-µ)&thinsp;&sup2;</sup>&frasl;<sub>2&sigma;&thinsp;&sup2;</sub></sup>
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{{Probability distribution
  | name      = Normal distribution
  | type      = density
  | pdf_image  = [[File:Probability Density Function.png|350px|Probability density function for the normal distribution]]<br /><small>The red curve is the ''standard normal distribution''</small>
  | cdf_image  = [[File:Normal_Distribution_CDF.png|350px|Cumulative distribution function for the normal distribution]]
  | notation  = [[File:Dist Normal Notation.png]]
  | pdf        = [[File:Dist Normal PDF.png]]
  | cdf        = [[File:Dist Normal CDF.png]]
  | quantile  = [[File:Dist Normal Quantile.png]]
  | mean      = µ
  | median    = µ
  | mode      = µ
  | variance  = σ²
  | skewness  = 0
  | kurtosis  = 0 <!-- DO NOT REPLACE THIS WITH THE OLD-STYLE KURTOSIS WHICH IS 3. -->
  }}
[[File:Standard Normal Equation.png|thumb|Curve Equation]]
[[File:Standard Normal CDF.png|thumb|CDF]]
[[File:Standard Normal PDF.png|thumb|PDF]]
[[File:Half Normal Distribution.png|thumb|500px|Half Normal Distribution Equations]]





Latest revision as of 17:34, 27 April 2015

The normal distribution is

f(x) = (1σ ) e-(x-µ) ²2σ ²


Normal distribution
Probability density function
Error creating thumbnail: File missing
The red curve is the standard normal distribution
Cumulative distribution function
Error creating thumbnail: File missing
Notation
PDF
CDF
Mean µ
Median µ
Mode µ
Variance σ²
Skewness 0
Kurtosis 0


Curve Equation
CDF
PDF
Half Normal Distribution Equations


  • 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.