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

In summary, the Standard Error of a coefficient is the standard deviation of the sampling distribution, which is estimated from a random sample. This estimate can be refined with additional sampling and the Central Limit Theorem states that the estimate will tend towards a normal distribution regardless of the population distribution. The Standard Error decreases with increasing sample size for a fixed sample standard deviation. However, it is important to note that the Standard Error is not the same as the standard deviation of the individual sample.
  • #1
musicgold
304
19
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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  • #2
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.
 
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  • #3
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.
 
  • #4
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.
 
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  • #5


I can understand your confusion about how Excel is able to anticipate a sampling distribution using just one sample. However, the answer lies in the fact that Excel uses statistical formulas and algorithms to estimate the sampling distribution based on the characteristics of the single sample provided. These formulas take into account the sample size, the variability of the data, and other statistical parameters to estimate the standard deviation of the sampling distribution and calculate the standard error. This is known as the Central Limit Theorem, which states that regardless of the population distribution, as the sample size increases, the sampling distribution will approach a normal distribution. Therefore, even with just one sample, Excel is able to anticipate a sampling distribution and provide an estimate of the standard error. It is important to note that this is an estimation and may not perfectly reflect the true sampling distribution, but it is a useful tool for statistical analysis and decision making. I hope this helps to clarify your doubts.
 

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

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

Excel uses the Central Limit Theorem to anticipate a sampling distribution using just one sample. This theorem states that as the sample size increases, the sampling distribution of the sample mean will approach a normal distribution regardless of the underlying distribution of the population.

2. Can Excel handle non-normal distributions when anticipating a sampling distribution?

Yes, Excel can handle non-normal distributions when anticipating a sampling distribution. This is because the Central Limit Theorem still holds for non-normal distributions, as long as the sample size is large enough.

3. How does Excel calculate the standard error of the mean for a single sample?

Excel uses the formula =STDEV.S(sample)/SQRT(n) to calculate the standard error of the mean for a single sample, where STDEV.S is the standard deviation of the sample and n is the sample size.

4. Why is it important to anticipate a sampling distribution using just one sample?

Anticipating a sampling distribution using just one sample allows us to make inferences about the population from which the sample was drawn. This is important because it allows us to estimate population parameters and make predictions based on the sample data.

5. Can Excel be used to generate a sampling distribution from a single sample?

Yes, Excel has built-in functions such as NORM.DIST and NORM.INV that can be used to generate a sampling distribution from a single sample. These functions use the mean and standard error of the sample to estimate the parameters of the sampling distribution.

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