Re: [R] (no subject)

From: Ben Bolker <>
Date: Wed, 28 May 2008 14:44:49 +0000 (UTC)

Philip Twumasi-Ankrah <nana_kwadwo_derkyi <at>> writes:

> Teds reply is a bit comforting and as indicated in my post,
> I am resorting to
> using "sample" but as an academic
> issue, does randomness preclude precision?
> Randomness should be in the sequence of zeros and ones and
> how they are simulated at each iteration of the
> process but not in the eventual nature of the distribution.
> I mean if I simulated a Normal (0, 1) and got a Normal(1.5, 2)
> these would be
> very different distributions. It
> is the same with simulating a Binomial(1, p=0.15) and getting
> Binomial(1, 0.154)

  It's impossible to have a sampler that is (1) Binomial(1,p) on each draw and (2) independent for each draw and (3) has exactly Np successes in N draws. For example, suppose you had drawn 99 Binomial(1,p=0.15) samples and had got(ten) 14 successes so far ... your last draw would be constrained to be 1 if you wanted property #3 to hold. So I guess the answer to your question is "yes" (except in the limit of infinitely large samples).

  Ben Bolker mailing list PLEASE do read the posting guide and provide commented, minimal, self-contained, reproducible code. Received on Wed 28 May 2008 - 18:00:22 GMT

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