Re: Inverted Bell Curve
- From: "Reef Fish" <Large_Nassau_Grouper@xxxxxxxxx>
- Date: 30 May 2006 21:58:33 -0700
Tasci wrote:
I'm clear on the fact that the sum of a random sampling from a range of
numbers say, 0 to 4, will distribute itself in the form of the bell
curve. That is, taking more numbers per sample increases the
likelihood of their sum being near the middle.
What you stated has something to do with the Central Limit Theorem.
Is there a different
function or relation besides 'sum' that I could use to set up a
situation where the extremes of 0 and 4 have the highest probability,
That' s a separate problem altogether about the shape of a distribution
being U-shaped, rather than "inverted Bell Curve". The "Bell curve"
is a bad enough mis-characterization without inverting it. :=)
The Beta distribution is a continuous distribution defined on the
interval
(0,1) which is versatile in its shapes: including your "bell" and U
shapes
as well as J-shaped and inverted J. I suppose you can rescale and
discretize the result to meet your distribution shapes.
Do you have a real context for your problem?
Knowing where your problem arises may help.
-- Bob.
and the center has the lowest chance of being hit? I want to make it
in this example so that the probability of getting 0 or 4 is very high,
and the probability of getting 2 is very low.
Standard bell curve;
____#____
____#____
__#_#_#__
#_#_#_#_#
0_1_2_3_4
What I w ant:
#_______#
#_______#
#_#___#_#
#_#_#_#_#
0_1_2_3_4
.
- References:
- Inverted Bell Curve
- From: Tasci
- Inverted Bell Curve
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