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Banach, Stefan, 1892-1945, Polish mathematician. He was educated at the Institute of Technology in Lviv; his doctoral thesis laid the foundations of modern functional analysis, which he continued to work at throughout his life. He also made fundamental contributions to general topology, set theory, the theory of measure and integration, and the general theory of linear spaces, or vector spaces, e.g., *Théorie des opérations linéaires* (1932). He introduced and developed the concept of complete normed linear spaces, now called Banach spaces.

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Licensed from Columbia University Press

Licensed from Columbia University Press

Banach's match problem is a classic problem in probability attributed to Stefan Banach.## Solution

## References

## External links

Suppose a mathematician carries two matchboxes at all times: one in his left pocket and one in his right. Each time he needs a match, he is equally likely to take it from either pocket. Suppose he reaches into his pocket and discovers that the box picked is empty. If it is assumed that each of the matchboxes originally contained $N$ matches, what is the probability that there are exactly $k$ matches in the other box?

Let $E$ denote the event that the man discovers the matchbox in his right pocket is empty and there are $k$ matches in the matchbox in his left pocket. This event occurs only if the $(N\; +\; 1)$th choice of the matchbox in his right pocket is made at the $N\; +\; 1\; +\; N\; -\; k$ trial.

Hence $E$ is a random variable with the negative binomial distribution, with parameters

- $p\; =\; 1/2,\; r\; =\; N\; +\; 1,\; n\; =\; 2N\; -\; k\; +\; 1,$

and so

- $P(E)\; =\; binom\{2N\; -\; k\}\{N\}\; left(frac\{1\}\{2\}right)^\{2N\; -\; k\; +\; 1\}.$

Since it is equally likely that the matchbox found to be empty is in the left pocket, the desired probability is

- $P(E)\; =\; binom\{2N\; -\; k\}\{N\}left(frac\{1\}\{2\}right)^\{2N\; -\; k\}.$

- Ross, Sheldon (2006).
*A First Course in Probability*. Seventh edition,

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Last updated on Tuesday August 14, 2007 at 00:04:48 PDT (GMT -0700)

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