Difference between revisions of "CumNormal"

(added integral equation and graph)
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Returns the cumulative probability  
 
Returns the cumulative probability  
p = Pr[x ≤ X]
+
:<math>p = Pr[x \le X] = {1\over{\sigma \sqrt{2\pi}}} \int_{-\infty}^x exp\left(- {1\over 2} {{(X-\mu)^2}\over\sigma^2}\right)</math>
 
for a [[Normal|normal distribution]] with a given mean and standard deviation.  Mean and stddev are optional and default to ''Mean = 0'', ''stddev = 1''.
 
for a [[Normal|normal distribution]] with a given mean and standard deviation.  Mean and stddev are optional and default to ''Mean = 0'', ''stddev = 1''.
CumNormal(1) - CumNormal( -1 ) → .683
+
:<code>CumNormal(1) - CumNormal( -1 )</code> → .683
 
i.e., 68.3% of the area under a normal distribution is contained
 
i.e., 68.3% of the area under a normal distribution is contained
 
within one standard deviation of the mean.
 
within one standard deviation of the mean.
 +
 +
[[image:CumNormalGraph.png]]
  
 
= Library =
 
= Library =

Revision as of 21:07, 14 January 2013


CumNormal(X,mean,stddev)

Returns the cumulative probability

[math]\displaystyle{ p = Pr[x \le X] = {1\over{\sigma \sqrt{2\pi}}} \int_{-\infty}^x exp\left(- {1\over 2} {{(X-\mu)^2}\over\sigma^2}\right) }[/math]

for a normal distribution with a given mean and standard deviation. Mean and stddev are optional and default to Mean = 0, stddev = 1.

CumNormal(1) - CumNormal( -1 ) → .683

i.e., 68.3% of the area under a normal distribution is contained within one standard deviation of the mean.

CumNormalGraph.png

Library

Advanced math

See Also

  • CumNormalInv -- the inverse cumulative density
  • Normal -- The normal distribution
  • Erf -- The closely related error function
  • Sigmoid(x) -- Another sigmoidal-shaped function
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