: Stefan Evert; R-help Mailing List
Subject: Re: [R] Small p from binomial probability function.
It is mysterious to me why the procedure proposed by Stefan Evert works.
It appears to work --- once you modify the call to binom.test() to have the
correct syntax. In a sequence of 1000 trials with random
Sounds like you want a 95% binomial confidence interval:
binom.test(N, P)
will compute this for you, and you can get the bounds directly with
binom.test(N, P)$conf.int
Actually, binom.test computes a two-sided confidence interval, which
corresponds roughly to 2.5 and 97.5
.
From: Stefan Evert [stefa...@collocations.de]
Sent: 10 October 2013 09:37
To: R-help Mailing List
Cc: Benjamin Ward (ENV)
Subject: Re: [R] Small p from binomial probability function.
Sounds like you want a 95% binomial confidence interval:
binom.test(N, P
October 2013 09:37
To: R-help Mailing List
Cc: Benjamin Ward (ENV)
Subject: Re: [R] Small p from binomial probability function.
Sounds like you want a 95% binomial confidence interval:
binom.test(N, P)
will compute this for you, and you can get the bounds directly with
binom.test
I've figured it out. It ***is*** obvious why Evert's procedure works.
Once you hold your head at the correct angle, as my first year calculus
lecturer
used to say.
The binom.test() confidence interval gives you the value of a random
variable
say U (for upper) such that
Pr(U p) = p0
Hi,
I got given some code that uses the R function pbionom:
p - mut * t
sumprobs - pbinom( N, B, p ) * 1000
Which gives the output of a probability as a percentage like 5, 50, 95.
What the code currently does is find me the values of t I need, by using the
above two code lines in a loop, each
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