- #1
Thejas15101998
- 43
- 1
I did not understand of the non-existence of variance.
What does it mean?
What does it mean?
yes.Dale said:I have never heard of that. Do you have a reference?
Thejas15101998 said:yes.
Refer to Philip Bevington's book on error analysis , pg 11 last paragraph.
micromass said:Can we please stop guessing what the OP means until he gives more information...
Stephen Tashi said:There would be a lot of stalled threads if we followed that policy consistently.
well yes it is the consequence of its slowly decreasing behavior for large deviations.Stephen Tashi said:The Cauchy distribution has no mean and hence (since the definition of the variance of a probability distribution requires that the mean exists) it has no variance.
For an experimental distribution, mean and variance can always be computed. I think you need to clarify what you mean when using the terms: average deviation, standard deviation, variance.Thejas15101998 said:
"No existence of Variance" refers to a situation where there is no difference or variation between two or more groups or samples.
"No existence of Variance" is measured using statistical tests such as the F-test or ANOVA, which compare the variances of the groups or samples in question. If the result of the test is not statistically significant, it indicates that there is no difference in variance between the groups.
In data analysis, "No existence of Variance" means that there is no evidence to suggest that the groups or samples being compared are different from each other. This could be due to chance or random sampling error.
"No existence of Variance" can occur due to various reasons such as the groups being truly homogeneous, the sample size being too small to detect differences, or the data being collected from a population with low variability.
"No existence of Variance" can impact research findings as it indicates that there is no significant difference between the groups being compared. This may lead to the rejection of the research hypothesis and a conclusion that there is no relationship between the variables being studied.