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binopdf

Binomial probability density function

Sintaxis

Y = binopdf(X,N,P)


Description

Y = binopdf(X,N,P) computes the binomial pdf at each of the values in X using the corresponding number of trials in N and probability of success for each trial in P. Y, N, and P can be vectors, matrices, or multidimensional arrays that all have the same size. A scalar input is expanded to a constant array with the same dimensions of the other inputs.

The parameters in N must be positive integers, and the values in P must lie on the interval [0, 1].

The binomial probability density function for a given value x and given pair of parameters n and p is

$$y=f(x|n,p)=\left(\begin{array}{c}n\\ x\end{array}\right)p^x{q}^{(n-x)}{I}_{(0,1,\mathrm{...},n)}(x)$$

where q = 1 – p. The result, y, is the probability of observing x successes in n independent trials, where the probability of success in any given trial is p. The indicator function I_(0,1,...,n)(x) ensures that x only adopts values of 0, 1, ..., n.

Examples

A Quality Assurance inspector tests 200 circuit boards a day. If 2% of the boards have defects, what is the probability that the inspector will find no defective boards on any given day?

binopdf(0,200,0.02)
ans =
  0.0176

What is the most likely number of defective boards the inspector will find?

defects=0:200;
y = binopdf(defects,200,.02);
[x,i]=max(y);
defects(i) 
ans =
  4

Capacidades ampliadas

Generación de código C/C++
Generar código C y C++ utilizando MATLAB® Coder™.

Arreglos GPU

Acelerar código mediante la ejecución en una unidad de procesamiento gráfico (GPU) utilizando Parallel Computing Toolbox™.

This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Consulte también

binocdf | binofit | binoinv | binornd | binostat | pdf

Temas

• Binomial Distribution

Introducido antes de R2006a