Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/Local_Theorem.R

Given n Bernoulli experiments, with success probability p, this function calculates the approximate probability that a successful event occurs exactly m times.

1 | ```
Local_Theorem(n, m, p)
``` |

`n` |
An integer value representing the number of repetitions of the Bernoulli experiment. |

`m` |
An integer value representing the number of times that a successful event occurs in the n repetitions of the Bernoulli experiment. |

`p` |
A real value with the probability that a successful event will happen in any single Bernoulli experiment (called the probability of success). |

Bernoulli experiments are sequences of events, in which successive experiments are independent and at each experiment the probability of appearance of a "successful" event (p) remains constant. The value of n must be high and the value of p must be small.

A real value representing the approximate probability that a successful event occurs exactly m times in n repetitions of a Bernoulli experiment.

Department of Mathematics. University of Oriente. Cuba.

Larisa Zamora and Jorge Diaz

Gnedenko, B. V. (1978). The Theory of Probability. Mir Publishers. Moscow.

Integral_Theorem, Poisson_Theorem.

1 2 3 4 5 6 7 8 9 10 11 12 | ```
Prob<-Local_Theorem(n=100,m=50,p=0.02)
Prob
## The function is currently defined as
function (n, m, p)
{
a <- n * p
b <- sqrt(a * (1 - p))
x <- (m - a)/b
P <- dnorm(x, 0, 1)/b
return(P)
}
``` |

ExpRep documentation built on July 4, 2017, 9:45 a.m.

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