Density 

Mean 

Variance 

Mode 
The Normal distribution is an unbounded continuous distribution. It is
sometimes called a Gaussian distribution or the bell curve. Because of
its property of representing an increasing sum of small, independent
errors, the Normal distribution finds many, many uses in statistics. It
is wrongly used in many situations. Possibly, the most important test
in the fitting of analytical distributions is the elimination of the
Normal distribution as a possible candidate.
The Normal distribution is used as an approximation for the Binomial
distribution when the values of n, p are in the appropriate range. The
Normal distribution is frequently used to represent symmetrical data,
but suffers from being unbounded in both directions. If the data is
known to have a lower bound, it may be better represented by suitable
parameterization of the Lognormal, Weibull or Gamma
distributions. If
the data is known to have both upper and lower bounds, the Beta
distribution can be used, although much work has been done on truncated
Normal distributions.
sigma =1; mean = 0
Generates a sample of the Normal distribution.
Name 
Type 
Description 
sigma 
double 
the shape parameter = standard deviation 
mean 
double 
the shift parameter = mean value 
Type 
Description 
double 
the generated sample 
Generates a sample of the Normal distribution with mean set
to
0. Is equivalent to normal(sigma, 0).
Name 
Type 
Description 
sigma 
double 
the shape parameter = standard deviation 
Type 
Description 
double 
the generated sample 
Generates a sample of the Normal distribution with mean set to 0 and sigma set to 1. Is equivalent to normal(1, 0).
Type 
Description 
double 
the generated sample 
Generates a sample of the Normal distribution using the specified random number generator.
Name 
Type 
Description 
sigma 
double 
the shape parameter = standard deviation 
mean 
double 
the shift parameter = mean value 
r 
java.util.Random 
the random number generator 
Type 
Description 
double 
the generated sample 
This document includes content from the Stat::Fit User's Manual. Copyright © 2016 Geer Mountain Software Corp.