Probability mass function 

Distribution 

Mean 

Variance 
The Binomial distribution is a discrete distribution bounded by [0,n]. Typically, it is used where a single trial is repeated over and over, such as the tossing of a coin. The parameter, p, is the probability of the event, either heads or tails, either occurring or not occurring. Each single trial is assumed to be independent of all others. For large n, the Binomial distribution may be approximated by the Normal distribution, for example when np>9 and p<0.5 or when np(1p)>9.
As shown in the examples above, low values of p give high probabilities for low values of x and visa versa, so that the peak in the distribution may approach either bound. The Binomial distribution has had extensive use in games, but is also useful in genetics, sampling of defective parts in a stable process, and other event sampling tests where the probability of the event is known to be constant or nearly so.
Generates a sample of the Binomial distribution.
Name 
Type 
Description 
p 
double 
the probability of the event occurrence 
n 
int 
the number of trials 
Type 
Description 
int 
the generated sample 
Generates a sample of the Binomial distribution with n set
to
1. Is equivalent to binomial(p, 1).
Name 
Type 
Description 
p 
double 
the probability of the event occurrence 
Type 
Description 
int 
the generated sample 
Generates a sample of the Binomial distribution using the specified random number generator.
Name 
Type 
Description 
p 
double 
the probability of the event occurrence 
n 
int 
the number of trials 
r 
java.util.Random 
the random number generator 
Type 
Description 
int 
the generated sample 
This document includes content from the Stat::Fit User's Manual. Copyright © 2016 Geer Mountain Software Corp.