ark <[EMAIL PROTECTED]>
>Subject: Re: diff in proportions
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Hi
On 16 Nov 2001, Rich Strauss wrote:
> I've just done some quick simulations in Matlab, constructing randomized
> null distributions of the t-statistic under both scenarious: (1) sample
> variances based on sample means vs. (2) variances about the pooled mean.
> Assuming I've done everything co
At 05:12 PM 11/16/01 +, you wrote:
>>On Thu, 15 Nov 2001, Jerry Dallal wrote:
>>> But, if the null hypothesis is that the means are the same, why
>>> isn't(aren't) the sample variance(s) calculated about a pooled
>>> estimate of the common mean?
I've just done some quick simulations in Matlab
>On Thu, 15 Nov 2001, Jerry Dallal wrote:
>> But, if the null hypothesis is that the means are the same, why
>> isn't(aren't) the sample variance(s) calculated about a pooled
>> estimate of the common mean?
Another thought on this... A simpler question is, for a one-sample
test of the hull hypot
> Jerry Dallal wrote:
>
>But, if the null hypothesis is that the means are the same, why
>isn't(aren't) the sample variance(s) calculated about a pooled
>estimate of the common mean?
I looked at this some years ago. The answer is straightforward: it
would be logically valid to do so but
In article <[EMAIL PROTECTED]>,
Jerry Dallal <[EMAIL PROTECTED]> wrote:
>Radford Neal wrote:
>> The difference is that when dealing with real data, it is possible for
>> two populations to have the same mean (as assumed by the null), but
>> different variances. In contrast, when dealing with b
In article <[EMAIL PROTECTED]>,
dennis roberts <[EMAIL PROTECTED]> wrote:
>At 08:03 PM 11/15/01 +, Radford Neal wrote:
>>Radford Neal:
>> >> The difference is that when dealing with real data, it is possible for
>> >> two populations to have the same mean (as assumed by the null), but
>> >> d
Hi
On Thu, 15 Nov 2001, Jerry Dallal wrote:
> But, if the null hypothesis is that the means are the same, why
> isn't(aren't) the sample variance(s) calculated about a pooled
> estimate of the common mean?
What you are testing is whether there is more variability between
groups than you would ex
At 08:03 PM 11/15/01 +, Radford Neal wrote:
>Radford Neal:
>
> >> The difference is that when dealing with real data, it is possible for
> >> two populations to have the same mean (as assumed by the null), but
> >> different variances. In contrast, when dealing with binary data, if
> >> the m
Radford Neal wrote:
>
> The difference is that when dealing with real data, it is possible for
> two populations to have the same mean (as assumed by the null), but
> different variances. In contrast, when dealing with binary data, if
> the means are the same in the two populations, the varianc
Dennis Roberts wrote:
>
> At 08:51 AM 11/15/01 -0600, jim clark wrote:
>
> >The Ho in the case of means is NOT about the variances, so the
> >analogy breaks down. That is, we are not hypothesizing
> >Ho: sig1^2 = sig2^2, but rather Ho: mu1 = mu2. So there is no
> >direct link between Ho and
I'm not really arguing for using the pooled stdev in this case, I'm just
trying to find out the reasons for significance testing procedures.
I think that what were discussing here is if we should use CIs BOTH
for stating effect sizes with errors AND for hypoyhesis testing. I read
a book by Mi
In article <[EMAIL PROTECTED]>,
dennis roberts <[EMAIL PROTECTED]> wrote:
>in the moore and mccabe book (IPS), in the section on testing for
>differences in population proportions, when it comes to doing a 'z' test
>for significance, they argue for (and say this is commonly done) that the
>sta
dennis roberts wrote:
>
> in the moore and mccabe book (IPS), in the section on testing for
> differences in population proportions, when it comes to doing a 'z' test
> for significance, they argue for (and say this is commonly done) that the
> standard error for the difference in proportions for
At 08:51 AM 11/15/01 -0600, jim clark wrote:
>The Ho in the case of means is NOT about the variances, so the
>analogy breaks down. That is, we are not hypothesizing
>Ho: sig1^2 = sig2^2, but rather Ho: mu1 = mu2. So there is no
>direct link between Ho and the SE, unlike the proportions
>example
At 04:26 PM 11/15/01 +0100, Rolf Dalin wrote:
>The significance test produces a p-value UNDER THE CONDITION
>that the null is true. In my opinion it does not matter whether we
>know it isn't true. It is just an assumption for the calculations. And
>these calculations do not produce exactly the s
Hi
On 15 Nov 2001, dennis roberts wrote:
> in the moore and mccabe book (IPS), in the section on testing for
> differences in population proportions, when it comes to doing a 'z' test
> for significance, they argue for (and say this is commonly done) that the
> standard error for the differen
Title: RE: diff in proportions
Dennis,
I am not sure about this, but here goes anyway. Since the decision making process is based on Type I error (Critical Point and p-value), and since Type I error is under the assumption that the Null Hypothesis is true, then the "p
in the moore and mccabe book (IPS), in the section on testing for
differences in population proportions, when it comes to doing a 'z' test
for significance, they argue for (and say this is commonly done) that the
standard error for the difference in proportions formula should be a POOLED
one .
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