Hi
Hope you know about the concept of Population and Sample in Statistics.
When we are doing hypothesis testing, we will be taking sample from the population and perform appropriate tests. After finishing the tests we have to approximate (project) those results to population.
For example, if a company is producing 39,750 units per day. What statisticians will do is, they will take a sample from that population and perform hypothesis testing also calculate the mean and SD (parameters) , called sample mean (x-Bar) and sample standard deviation (s).
You do not want to sit and calculate mean and standard deviation for your population data.
Once it is calculated for sample, it has to be replaced for population. You cannot simply substitute the value of sample to the population. Here comes the property of estimators called unbiased-ness. Says that, once you calculated for sample and while estimating (projecting) to the population, the sample parameter has to satisfy the following condition it is
Expectation [sample parameter] = Population Parameter
E[x-Bar] = meu
In this sense, If we use
You cannot replace for Population S.D. Sigma
i. e.,
That’s why we use
Now we can replace our calculated value of sample standard deviation to the population parameter sigma.
I can send you, if you are looking for detailed proof.
Regards
Yuvaraj.
thivya praba <thivya_friends@ yahoo.co. in> wrote:
|
Hi friends,
I would be helpful if any one can clear my doubts.
we use (n-1) d.f in S and n in s. v replace s in place of S, if v r not known abt the pop variance. but my doubt s,
1. if v r known with n, v can find both S and s.
then wat s t necessity of s?
2.why does S has d.f (n-1) and s as n?
Thanks in advance. |
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