Gaussian distribution (z)

Mark Brownell gizmotron at earthlink.net
Wed Oct 22 14:12:43 EDT 2008


>Date: Tue, 21 Oct 2008 15:03:17 -0700
>From: Timothy Miller <gandalf at doctorTimothyMiller.com>

>Greetings,
>
>I'm interested an a modest statistics demonstration, but I can't  
>figure out how do to the math myself.
>
....
>
>Hmmmm... I wonder if some website somewhere would do the work for me.  
>That could work... I looked around, but didn't find anything.
>
>Thanks in advance.
>
>Tim Miller
>

Hi Tim,

(Digest mode) please cc me

http://en.wikipedia.org/wiki/Normal_distribution

http://en.wikipedia.org/wiki/Clustering_illusion

http://en.wikipedia.org/wiki/Gambler_fallacy

I've used Rev to research the nature of randomness. The smaller the sample size (z) the more the clustering illusion and the gambler's fallacy plays a part in attempting to understand randomness.

Rev sets the random seed every time RunRev is started up. It then uses that same seed for the entire time that you use random(#).

random(22) -- returns a number between 1 and 22

set the randomSeed to 4570422

I would do this to achieve a more true random number:

put random(999999999999999999) into zSeedVar
set the randomSeed to zSeedVar
put random(z) into zHoldVar


You can make your list of results and use the standardDeviation() function.

standardDeviation(8,10,12) -- returns 2

odds are simple: 

50% X 50% = 25%

50% X 50% X 50% = 12.5%

50% X 50% X 25% = 6.25%

I'm not clear where to start. Almost all probability can be figured with simple arithmetic.

Mark






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