[R] One-sample test for p

[rr400]

Thanks for your responses. I know it is bad form asking about these things
but i was really having trouble getting my head around it, and i wanted to
make sure that the cause wasn't due to the commands i was entering into R.
At least now i know it's a conceptual error i am making rather than a
technical one. 

Thanks again for your help. R.

Duncan Murdoch-2 wrote:
> 
> On 10/16/2008 7:35 AM, Peter Dalgaard wrote:
>> rr400 wrote:
>>> Hi, i am doing a statistics course and am having trouble with an
>>> exercise
>>> where i need to determine whether my success rate at something is higher
>>> than 80%. 
>>> I was successful in 29 out of 60 trials, so these were the commands i
>>> entered into R:
>>>> n=60
>>>> p.hat=29/n
>>>> p.0=0.8
>>>> se.0=sqrt(p.0*(1-p.0)/n)
>>>> z=(p.hat-p.0)/se.0
>>>> print(z)
>>> Which returned:
>>> [1] -6.132224
>>>> 1-pnorm(z)
>>> Which returned
>>> [1] 1
>>> 
>>> My problem is that i am meant to state a null and alternative hypothesis
>>> which at the moment i have stated as  p>0.8 (null) and p≤0.8
>>> (alternative).
>>> As things stand, though, a p-value of 1 suggests i should reject the
>>> null
>>> hypothesis which can't be right since i am obviously successful less
>>> than
>>> 80% of the time. 
>>> I am not sure where i am getting muddled. Any advice would be greatly
>>> appreciated. Thanks!
>> 
>> This isn't really about R, and maybe it is homework, but now that we got 
>> you in the appropriate frame of mind:
>> 
>> (a) p values should look at "this or more unfavourable" events. You have 
>> arranged things so that that translates to -6.13 or _lower_. I.e. you're 
>> looking at the wrong tail.
> 
> I think he was looking at the right tail, since his p value was 1.  Your 
> comment (b) is the important one; comment (c) might not be allowed by 
> his instructor, which is one reason I'm always reluctant to give advice 
> on other people's homework problems.
> 
> Duncan Murdoch
> 
>> 
>> (b) Make sure you get your accept/reject logic right. You _reject_ the 
>> null when data would be _un_likely if the null hypothesis were true.
>> 
>> (c) You might also want to play with binom.test and prop.test
>>
> 
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