Hp 50g Graphing Calculator Manual do Utilizador descarregar pdf (Página 553)

100

101

Page 17-4

function (pmf) is represented by f(x) = P[X=x], i.e., the probability that the

random variable X takes the value x.

The mass distribution function must satisfy the conditions that

f(x) >0, for all x,

and

A cumulative distribution functio

n (cdf) is defined as

Next, we will define a number of functions to calculate discrete probability

distributions. We suggest that you create a sub-directory, say,

HOME\STATS\DFUN (Discrete FUNctions) where we will define the probability

mass function and cumulative distribution function for the binomial and Poisson

distributions.

Binomial distribution

The probability mass function of the binomial distribution is given by

where (

) = C(n,x) is the combination of n elements taken x at a time. The

values n and p are the parameters of the distribution. The value n represents

the number of repetitions of an experiment or observation that can have one of

two outcomes, e.g., success and failure. If the random variable X represents the

number of successes in the n repetitions, then p represents the probability of

getting a success in any given repetition. The cumulative distribution function

for the binomial distribution is given by

0.1)( =

∑

xall

∑

≤

=≤=

kfxXPxF )(][)(

nxpp

xpnf

xnx

,...,2,1,0,)1(),,( =−⋅⋅

⎟

⎠

⎞

⎜

⎝

⎛

−

1 2 ... 548 549 550 551 552 553 554 555 556 557 558 ... 886 887

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