How does Excel anticipate a sampling distribution using just one sample?

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Discussion Overview

The discussion revolves around the concept of Standard Error (SE) in statistics, particularly how Excel calculates it using a single sample. Participants explore the relationship between a sample's standard deviation and the anticipated sampling distribution, as well as the implications of the Central Limit Theorem.

Discussion Character

  • Conceptual clarification, Technical explanation, Debate/contested

Main Points Raised

  • One participant expresses confusion about how Excel can calculate the Standard Error when only one sample is available, questioning the anticipation of a sampling distribution without knowledge of the population.
  • Another participant explains that the Standard Error of the mean is calculated as SE = s/√n, where s is the sample standard deviation, suggesting that a random sample can provide a valid estimate of the population standard deviation (σ).
  • There is a clarification that while SE is indeed the standard deviation of the sampling distribution, it differs from the standard deviation of the individual sample, which adds to the confusion regarding terminology.

Areas of Agreement / Disagreement

Participants generally agree on the definition of Standard Error and its calculation, but there is some confusion regarding the distinction between the standard deviation of the sample and the standard deviation of the sampling distribution.

Contextual Notes

The discussion highlights potential misunderstandings related to statistical terminology and the assumptions underlying the estimation of population parameters from a single sample.

musicgold
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Hi,

I know that Standard Error of a coefficient is the standard deviation of the sampling distribution associated with the coefficient. I understand the concept.

What puzzles me is this: We have just one random sample to work with. The calculator or Excel doesn’t have any info on the actual population or any other sample. Then how can it anticipate a sampling distribution and calculate its standard deviation to give us the Standard Error?

Thanks.
 
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musicgold said:
Hi,

I know that Standard Error of a coefficient is the standard deviation of the sampling distribution associated with the coefficient. I understand the concept.

What puzzles me is this: We have just one random sample to work with. The calculator or Excel doesn’t have any info on the actual population or any other sample. Then how can it anticipate a sampling distribution and calculate its standard deviation to give us the Standard Error?

Thanks.

The standard error of the mean is [itex]SE = s/\sqrt {n}[/itex] where s is the sample standard deviation. In other words you are estimating the population [itex]\sigma[/itex] from the sample of size n. The concept is that a truly random sample can yield a valid estimate of [itex]\sigma[/itex]. Obviously, as an estimate, it can be refined by additional sampling. The Central Limit Theorem states that the estimates of the mean will tend toward a normal distribution regardless of the population distribution. It's clear that the SE declines with increasing n for fixed s.
 
Last edited:
Thanks SW VandeCarr.


In other words you are estimating the population σ from the sample of size n.
I thought SE is the std dev of the sampling distribution.
 
musicgold said:
Thanks SW VandeCarr.
I thought SE is the std dev of the sampling distribution.

Yes, but that's not the same as the sd of the individual sample. The terminology is a bit confusing. I suggest you look it up.
 
Last edited:

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