[Resultados pqrs]Tema Piloto

2016

Roberth Tampoa

25.149.524

Num.

Hipergeométrica

4 N = 25N1 = 8n = 6x = 4

P(X=x)

P(X=x) = (N1Cx) (N-N1Cn-x) (NCn)-1 for x = max (0, n-N+N1), ... , min (n, N1)P(X = 4) = 0,053754940711Expectation = nN1/N = 1,92Variance = nN1(N - N1)(N - n) / [N2(N - 1)] = 1,0336Standard deviation = 1,016661202171

Has applications in finite population sampling: if N1 out of N objects have a certain property and n objects are sampled without replacement, the number of sampled objects with the property has a hypergeometric distribution

Num.

Binomial

4 n = 21p = 0,25x = 13

P(X=x)

P(X=x) = (nCx) px (1-p)n-x for x = 0,1, ..., nP(X = 13) = 0,000303566114Expectation = np = 5,25Variance = np(1 - p) = 3,9375Standard deviation = 1,984313483298Moment generating function M(t) = (1 - p + pet)n

The distribution of the total number of successes in a series of n independent Bernoulli trials

Num Poisson

.4 λ = 8

x = 6P(X=x)

P(X=x) = e- x / x! for x = 0, 1, ....P(X = 6) = 0,122138215463Expectation = = 8Variance = = 8Standard deviation = 2,828427124746Moment generating function M(t) = exp[(et - 1)]

Used in modeling the number of occurrences of an event in a given time interval