Hypothesis testing for std. deviation (SD)

Click For Summary

Discussion Overview

The discussion revolves around the hypothesis testing for standard deviation (SD) in statistics, specifically questioning why the Chi-square distribution is used instead of a sampling distribution of standard deviations. Participants explore the theoretical underpinnings and practical implications of different approaches to hypothesis testing related to SD.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • Some participants express confusion about why a sampling distribution of SDs is not used for hypothesis testing, as is done for means.
  • One participant questions the specific hypothesis being tested when using the Chi-square distribution, seeking clarification on the problem context.
  • Another participant mentions that the hypothesis test is intended to verify the standard deviation of a population and seeks to understand the rationale behind using the Chi-square statistic.
  • A participant explains that using a 1-to-1 function allows for hypothesis testing about the sample variance instead of the sample standard deviation, suggesting that this can simplify the testing process.
  • It is noted that different families of population distributions can lead to different families of sampling distributions for sample variances and standard deviations, indicating that there is no single distribution applicable to all cases.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the appropriateness of using the Chi-square distribution versus a sampling distribution of SDs for hypothesis testing. Multiple viewpoints and questions remain unresolved.

Contextual Notes

Participants highlight the complexity of the topic, noting that the distribution of sample standard deviations may vary depending on the underlying population distribution, which complicates the use of a single distribution for hypothesis testing.

musicgold
Messages
303
Reaction score
19
Hi,

What I know: In a hypothesis test for the mean, we compare a sample mean with a hypothetical sampling distribution of means. And depending on how far it is away from the mean of the sampling distribution, we attribute it the probability of getting that value purely by chance.

What I don't understand - In a hypothesis test for the SD, why don't we compare the sample SD with a sampling distribution of SDs? (instead, I have seen people using the the Chi sq. distribution)

As per the applet on the following web page, even the sampling distribution of SDs appears normally distributed around the population SD value. So why is it not used?
[/PLAIN]
http://www.stat.tamu.edu/~west/ph/sampledist.html[/URL]

Thanks.
 
Last edited by a moderator:
Physics news on Phys.org
musicgold said:
Hi,

What I know: In a hypothesis test for the mean, we compare a sample mean with a hypothetical sampling distribution of means. And depending on how far it is away from the mean of the sampling distribution, we attribute it the probability of getting that value purely by chance.

If you did that, what hypothesis would you be testing?

What I don't understand - In a hypothesis test for the SD, why don't we compare the sample SD with a sampling distribution of SDs? (instead, I have seen people using the the Chi sq. distribution)

It isn't clear what hypothesis you are testing. What specific problem are you talking about that was solved using the Chi square distribution?

As per the applet on the following web page, even the sampling distribution of SDs appears normally distributed around the population SD value. So why is it not used?
[/PLAIN]
http://www.stat.tamu.edu/~west/ph/sampledist.html[/URL]
How did you use that applet to create a histogram of sample standard deviations?
 
Last edited by a moderator:
Thanks Stephen,
Stephen Tashi said:
It isn't clear what hypothesis you are testing. What specific problem are you talking about that was solved using the Chi square distribution?

I am talking about the hypothesis test used to verify the standard deviation of a population.
Here is one example.

My question is why don't we use a sampling distribution of standard deviations (SD) to compare the sample SD, as we do for other statistics like mean or median. Why do we need to use the Chi Sq. statistic?
 
If f(x) is a 1-to-1 function and X is a random variable then the probability of the event X < v is the same as the probability of the event f(X) < f(v). If you are doing a hypothesis test about X and the distribution of f(X) is easiest to use then its simpler to formulate the test as a hypothesis about f(X). The sample standard deviation and the sample variance are related by a 1-to-1 function, so , when it's simpler, we can use the sample variance to test hypotheses about the sample standard deviation.

This PDF suggests that when sampling from normal populations we might also use the distribution of the standard deviation directly:
http://www.google.com/url?sa=t&rct=...rNp_Tb9hssxhbRQ&bvm=bv.58187178,d.aWc&cad=rja

Different families of population distributions can have different families of sampling distributions for their sample variances and sample standard deviations. Normally distributed populations have chi-squared distributions for their sample variances. Other families of distributions may have sample variances that are not chi-squared. (So one cannot speak of "the" distribution of the sample standard deviation as if there was some type of distribution for it that applies to all situations.)
 
  • Like
Likes   Reactions: 1 person

Similar threads

  • · Replies 4 ·
Replies
4
Views
3K
Replies
20
Views
3K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 7 ·
Replies
7
Views
3K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 20 ·
Replies
20
Views
4K
  • · Replies 11 ·
Replies
11
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K