Can Higher Order Central Moments Be Zero When Variance Approaches Zero?

AI Thread Summary
The discussion centers on whether higher order central moments can be zero when the variance of a random variable approaches zero as sample size increases. One participant suggests that as variance decreases, higher order moments should also decrease more rapidly. Another clarifies that a random variable has a fixed distribution that does not depend on sample size, raising questions about the interpretation of the original query. The conversation explores different scenarios, including the behavior of sampling distributions and the nature of degenerate distributions with zero variance. Ultimately, the relationship between variance and higher order moments in statistical contexts is complex and requires careful consideration.
benjaminmar8
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Hi, all,

Let's assume a random variable's variance is zero as sample size tends to infinity somehow, can I say that its higher order central moments are also zero as the sample size tends to infinity?

Thks a lot
 
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That makes sense to me given that when the variance gets very small the higher order central moments should tend to zero faster then the variance because the square of a small quantity is even smaller then that small quantity.
 
Your question really doesn't make sense: a random variable has a single distribution (normal distribution, chi-square distribution, etc) and does not depend on a sample size. if you respond "t-distribution" - that doesn't fit your comment: t-distributions are INDEXED by their degrees of freedom, but there is no requirement that there be a link to sample size.do you mean this:
if, in a series of samples of increasing sample size, if the sample variance tends to zero then all higher-order moments tend to zero?

or do you mean this:

if a (degenerate) distribution has variance zero, are all higher-order moments equal to zero.

One other possibility: are you talking about the behavior of SAMPLING distributions as the sample size tends to infinity?
 
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