Re: When Can We Really Use CLT & Student t

2001-11-28 Thread Jerry Dallal
Ronny Richardson wrote: > > As I understand it, the Central Limit Theorem (CLT) guarantees that the > distribution of sample means is normally distributed regardless of the > distribution of the underlying data as long as the sample size is large > enough and the population standard deviation is

Re: When Can We Really Use CLT & Student t

2001-11-28 Thread Jerry Dallal
> "Kaplon, Howard" wrote: > > What many authors do, I believe, is employ the Law of Large > Numbers, and say that for n sufficiently large, the probability > approaches 0 that | sigma - s | is different from 0. That is > sigma and s may be interchanged with "minimal" probability of any > change

Re: When Can We Really Use CLT & Student t

2001-11-23 Thread Herman Rubin
In article <[EMAIL PROTECTED]>, Kaplon, Howard <[EMAIL PROTECTED]> wrote: >This is a multi-part message in MIME format. >It has been a long time; so if I am wrong, please fan the flames gently. >The derivation of the t distribution is from the ratio of a Normal(0,1) >over the square root of a C

Re: When Can We Really Use CLT & Student t

2001-11-23 Thread Herman Rubin
In article <[EMAIL PROTECTED]>, Ronny Richardson <[EMAIL PROTECTED]> wrote: >As I understand it, the Central Limit Theorem (CLT) guarantees that the >distribution of sample means is normally distributed regardless of the >distribution of the underlying data as long as the sample size is large >eno

Re: When Can We Really Use CLT & Student t

2001-11-21 Thread Rich Ulrich
On 21 Nov 2001 10:18:01 -0800, [EMAIL PROTECTED] (Ronny Richardson) wrote: > As I understand it, the Central Limit Theorem (CLT) guarantees that the > distribution of sample means is normally distributed regardless of the > distribution of the underlying data as long as the sample size is large >

Re: When Can We Really Use CLT & Student t

2001-11-21 Thread Jay Warner
Ronny Richardson wrote: > As I understand it, the Central Limit Theorem (CLT) guarantees that the > distribution of sample means is normally distributed regardless of the > distribution of the underlying data as long as the sample size is large > enough and the population standard deviation is kn

Re: When Can We Really Use CLT & Student t

2001-11-21 Thread Gus Gassmann
Ronny Richardson wrote: > As I understand it, the Central Limit Theorem (CLT) guarantees that the > distribution of sample means is normally distributed regardless of the > distribution of the underlying data as long as the sample size is large > enough and the population standard deviation is kn

Re: When Can We Really Use CLT & Student t

2001-11-21 Thread Vadim and Oxana Marmer
On 21 Nov 2001, Ronny Richardson wrote: > As I understand it, the Central Limit Theorem (CLT) guarantees that the > distribution of sample means is normally distributed regardless of the > distribution of the underlying data as long as the sample size is large > enough and the population standard

RE: When Can We Really Use CLT & Student t

2001-11-21 Thread Kaplon, Howard
Title: RE: When Can We Really Use CLT & Student t It has been a long time; so if I am wrong, please fan the flames gently. The derivation of the t distribution is from the ratio of a Normal(0,1) over the square root of a ChiSquare divided by its degrees of freedom.     t =  [(x

Re: When Can We Really Use CLT & Student t

2001-11-21 Thread Dennis Roberts
At 12:49 PM 11/21/01 -0500, Ronny Richardson wrote: >As I understand it, the Central Limit Theorem (CLT) guarantees that the >distribution of sample means is normally distributed regardless of the >distribution of the underlying data as long as the sample size is large >enough and the population s