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erika01
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Bernoulli Distribution:
Parameters: p = prob. of success = (0 ≤ p ≤ 1)
Range = x {0,1}
Probability mass function f of this distribution is:
f(x) = 1p if x = 0 ; p if x = 1 ; 0 otherwise
 Mean = p
 Variance = p (1p)

Binomial Distribution:
Notation: B(n,p)
Parameters: p = 0 < p < 1 (+integer)
n = numer of trials = n > 0
Range = x={0,1,...n}
Probability mass function (pmf) is:
(n/p) p^{k }(1p)^{nk
}
 Mean = np
 Variance = np (1p)

Exponential Distribution:
*x = t ; 1/a = delta
Parameters: a = (1/x) sacale parameter
Range = x= {0 ≤ x ≤ ∞}
Pmf = f(x) = 1/a * e^{x/a
}
 Mean = delta^{1 }or 1/delta *delta = λ
 Variance = delta^{2} or (1/delta)^{2 }= (1/λ)^{2}

Geometric Distribution:
Parameter: p = probability of success = (0 < p < 1)
Range: x = { 1,2,3…∞}
Probability mass function (pmf) is:
f(x) = (1p)^{x1} p
 Mean = 1/p
 Variance = (1p)/ p^{2}

Poisson Distribution:
Notation: Pois(λ)
Parameter: λ = mean ; λ >0
Range: x = {0, 1, 2, 3, …, ∞}
Probability mass function (pmf) is:
(λ^{k }/ k!) * e^{λ}

