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Probability of a binomial distributed variable

Posted 2 days ago

Dear community,
if I enter
probability 0 <= x <= 199 if x is binomial with n = 629 and p = 1/3
I have no result.
If I enter
probability 0 <= x <= 199 if x is binomial with n = 629 and p = 0,3333333333
I got a result.
Any inspiration, what I did wrong?
Regards.

6 Replies

I do get a result with

Probability[0 <= x <= 199, 
 Distributed[x, BinomialDistribution[629, 1/3]]]

It is a rather complicated rational number. I can apply N to get a floating point approximation.

Maybe you had a semicolon ; at the end of the expression? That suppresses the display of the output.

POSTED BY: Gianluca Gorni

Thanks Gianluca, no, I haven't put a semicolon at the end. I tried to solve the Problem wit my handy and it works. Best regards Joachim

Or maybe the exact value computation timed out on Wolfram|Alpha but the numeric one did not?

POSTED BY: Daniel Lichtblau

I obtain the result in less than 6 seconds (rather long, but not really complicated)

probability 0 <= x <= 199 if x is binomial with n = 629 and p = 1/3

2790202042683170027396338572156271486236764921820554406324053343438420\ 7473524012382076372430640929027629909848334225903726967528396496546094\ 2768804990201714967763531874391873967728927521481203010698948463470386\ 5556684010030811850825222228971811003257372984250289096178370247660188\ 8824446582320529408/\ 1428981838579134870963576158997950040247615937024229320041839443209485\ 7063291801552419719892590341365005232809905728568571532045291896518962\ 0416249357065663843887173052694852955236403957825594931793818273072298\ 1380571684806205514443614319046207595729139902191275491143892128100897\ 71517714979850768987

In[3]:= N[%]

Out[3]= 0.195258

POSTED BY: Tomas Garza

Hello again, I used the alpha widget: Berechnen von Werten der Binomialverteilung. No result. Regards.

Incidentally, the normal approximation to the binomial gives the value 0.183472 which, compared to the 0.195258 obtained directly, has a relative error of 6.4%. Too large, maybe..., depending, of course, on the purpose of the exercise. But, of course, it takes almost the same time and effort to calculate both results. So, come to think of it, nowadays the central limit theorem is perhaps as outdated as the tables of logarithms (for numerical approximations purposes).

POSTED BY: Tomas Garza
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