Thanks for your answers
.......................................................................
Now, I would like to know what I can to know more to explain for my students about the Galton Board (quicunx) more than this
explanation of this site http://www.stattucino.com/berrie/dsl/Galton.html
This applet simulates Galton's Board, in which balls are dropped through a triangular array of nails. This device is also called a quincunx. Every time a ball hits a nail it has a probability of 50 percent to fall to the left of the nail and a probability of 50 percent to fall to the right of the nail.
The piles of balls which accumulate in the slots beneath the triangle will resemble a binomial distribution. To reach the bin at the far left the ball must fall to the left every time it hits a nail.
Because Galton's board consists of a series of experiments the piles in the slots are the sum of random variables. Therefore, this simulation provides also an illustration of the central-limit theorem, which states that the distribution of the sum of n random variables approaches the normal distribution when n is large. When we add more rows of nails to the board the approximation would be better.
TIA
Ivan
.................................................................................................................................
At 12:03 PM 8/30/2003 +0000, you wrote:
"David Heiser" <[EMAIL PROTECTED]> wrote in
news:[EMAIL PROTECTED]:
>
> <[EMAIL PROTECTED]> wrote in message
> news:[EMAIL PROTECTED]...
>> Thanks for your answer Dr Karl W., but I am lookinf for an
>> explanation about the importance of this Galton Board.
>> The real importance of this Galton Board in relation to Statistical
> history
>> and/or real life
>> Thanks again
>> Ivan
> -----------------------------------------------------------------------
> ----- -----------------
> We're talking about 1893 when they didn't have electronics,
> Galton's board of nails, shown as an illustration in his book, was a
> device to show that random events (impacts on balls) tended to a
> normal distribution of final position. >
> David Heiser
>
Isn't the final result a normal approximation of the binomial distribution?
>
.
.
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