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From: statsleppermessiah on 18 Apr 2010 18:54
My question is actually this (given my previous post):

1)If we _do_ know the true population mean, then why do

we care about the mean, and overall distribution of

sampling data.


2)If we _do not_ know the true population mean:

How do we estimate it from the CLTheorem, if the

intervals are centered at the true population mean--

which we do not know.?

TIA,

LM.
From: Bacle on 18 Apr 2010 19:25
> My question is actually this (given my previous
> post):
>
> 1)If we _do_ know the true population mean, then why
> y do
>
> we care about the mean, and overall distribution
> on of
>
> sampling data.
>
>
> 2)If we _do not_ know the true population mean:
>
> How do we estimate it from the CLTheorem, if the
>
> intervals are centered at the true population
> ion mean--
>
> which we do not know.?
>
> TIA,
>
> LM.

Look up: "Confidence Intervals". This is the whole
point. I do not understand either,tho, the point of
figuring out, or knowing, the distribution of the
sampling data when we already know the true population
mean.
From: porky_pig_jr on 19 Apr 2010 01:47
On Apr 18, 10:54 pm, statsleppermessiah <none...(a)none.com> wrote:
> My question is actually this (given my previous post):
>
>  1)If we _do_ know the true population mean, then why do
>
>   we care about the mean, and overall distribution of
>
>   sampling data.

In case of normal distribution we are also interested in population
variance.

>
>  2)If we _do not_ know the true population mean:
>
>    How do we estimate it from the CLTheorem, if the
>
>    intervals are centered at the true population mean--
>
>    which we do not know.?
>

But the confidence intervals are *not* centered at the true population
mean. When we compute CI with, say, alpha = 0.05, we only claim that
we're 95% sure that the true mean is *somewhere* in the CI. How do we
compute CI from the CLT? Take any textbook on math stats (like Hogg
and Craig), it's all there.

>    TIA,
>
>     LM.

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