# R: st: probability mass function for a binomial distribution

 From "Carlo Lazzaro" To Subject R: st: probability mass function for a binomial distribution Date Sun, 29 Jun 2008 19:10:44 +0200

```Dear Nick,
thanks a lot for making it simpler than I was figured out it to be.

I agree with you about the theoretical endless row of defined functions
which may be included in a statistical package: a reasonable compromise
between users'neeeds and their statistical background is the way to go for
delivering an effective and efficient software.

Kind Regards,

Carlo

-----Messaggio originale-----
Da: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Nick Cox
Inviato: domenica 29 giugno 2008 17.27
A: statalist@hsphsun2.harvard.edu
Oggetto: RE: st: probability mass function for a binomial distribution

What is available as a defined function shows up a trade-off problem. It
wouldn't be difficult to define a thousand functions, but then some
people might complain about the complexity of the list and the
difficulty of finding a solution.

Otherwise put, I guess the answer to Carlo's question is that Stata
users -- unlike spreadsheet users, it seems --- are paid the compliment
of knowing enough statistics to work this out from first principles:

gen double bmp = p^k * (1 - p)^(20 - k) * comb(20, k)

Note in passing two other details:

I prefer to use -double-s here.

Putting constants into variables isn't necessary:

gen double bmp = 0.2^k * 0.8^(20 - k) * comb(20, k)

In cases like this the advantage of a canned function over a one-line
solution using another canned function would be pretty small.

Nick
n.j.cox@durham.ac.uk

[previous message deleted to avoid Buffer overrun warning]

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```