## a simpler (?) birthday problem

Posted in Books, Kids, Statistics with tags , , , , , , , on April 9, 2022 by xi'an

A monthly birthday problem from the Riddler:

What was the probability that none of the 40 people had birthdays this month? What is the probability that there is at least one month in the year during which none of the 40 people had birthdays (not necessarily this month)?

Assuming the same number of days in all months, the probability that one individual is not born in March is 1/12 and hence the probability that none of 40 (independent!) persons are not born in March is (11/12)⁴⁰, about 3%. The second question can be solved by reading Feller’s chapter on the combination of events (1970, Chapter IV, p.102). The probability that all months are seeing at least one birthday is

$\sum_{i=0}^{12} (-1)^i {12\choose i}(1-i/12)^{40}=0.6732162$

which can be checked by a quick R simulation. The complement 0.326 is thus close to 11 x 0.03!

## random walk on a torus [riddle]

Posted in Books, Kids, pictures with tags , , , , , , , , , on September 16, 2016 by xi'an

The Riddler of this week(-end) has a simple riddle to propose, namely given a random walk on the {1,2,…,N} torus with a ⅓ probability of death, what is the probability of death occurring at the starting point?

The question is close to William Feller’s famous Chapter III on random walks. With his equally famous reflection principle. Conditioning on the time n of death, which as we all know is definitely absorbing (!), the event of interest is a passage at zero, or any multiple of N (omitting the torus cancellation), at time n-1 (since death occurs the next time). For a passage in zero, this does not happen if n is even (since n-1 is odd) and else it is a Binomial event with probability

${n \choose \frac{n-1}{2}} 2^{-n}$

For a passage in kN, with k different from zero, kN+n must be odd and the probability is then

${n \choose \frac{n-1+kN}{2}} 2^{-n}$

which leads to a global probability of

$\sum_{n=0}^\infty \dfrac{2^n}{3^{n+1}} \sum_{k=-\lfloor (n-1)/N \rfloor}^{\lfloor (n+1)/N \rfloor} {n \choose \frac{n-1+kN}{2}} 2^{-n}$

i.e.

$\sum_{n=0}^\infty \dfrac{1}{3^{n+1}} \sum_{k=-\lfloor (n-1)/N \rfloor}^{\lfloor (n+1)/N \rfloor} {n \choose \frac{n-1+kN}{2}}$

Since this formula is rather unwieldy I looked for another approach in a métro ride [to downtown Paris to enjoy a drink with Stephen Stiegler]. An easier one is to allocate to each point on the torus a probability p[i] to die at position 1 and to solve the system of equations that is associated with it. For instance, when N=3, the system of equations is reduced to

$p_0=1/3+2/3 p_1, \quad p_1=1/3 p_0 + 1/3 p_1$

which leads to a probability of ½ to die at position 0 when leaving from 0. When letting N grows to infinity, the torus structure no longer matters and the probability of dying at position 0 implies returning in position 0, which is a special case of the above combinatoric formula, namely

$\sum_{m=0}^\infty \dfrac{1}{3^{2m+1}} {2m \choose m}$

which happens to be equal to

$\dfrac{1}{3}\,\dfrac{1}{\sqrt{1-4/9}}=\dfrac{1}{\sqrt{5}}\approx 0.4472$

as can be [unnecessarily] checked by a direct R simulation. This √5 is actually the most surprising part of the exercise!

## not only defended but also applied (rev’d)

Posted in Statistics with tags , , , on April 16, 2012 by xi'an

Following a very positive and encouraging review by The American Statistician of our paper with Andrew Gelman on Feller’s misrepresentation of Bayesian statistics in the otherwise superb Introduction to Probability Theory , we have submited a revised version, now posted on arXiv. Hopefully, we will be able to publish this historic-philosophical note in The American Statistician, and maybe even get a discussion paper on the issue of misconceptions on Bayesian analysis.

## “Not only defended but also applied”: The perceived absurdity of Bayesian inference

Posted in Books, Statistics, University life with tags , , , , , , , on October 13, 2011 by xi'an

After a first unsuccessful attempt at publishing a note on the great Willliam Feller’s dismissive attitude towards Bayesian statistics, in An Introduction to Probability Theory and Its Applications, and more broadly about misconceptions on Bayesianism, jointly with Andrew Gelman, last year, we have rewritten some of it and resubmitted to The American Statistician. It has also been re-arXived. Here is the abstract:

Abstract. The missionary zeal of many Bayesians has been matched, in the other direction, by a view among some theoreticians that Bayesian methods are absurd—not merely misguided but obviously wrong in principle. We consider several examples, beginning with Feller’s classic text on probability theory and continuing with more recent cases such as the perceived Bayesian nature of the so-called doomsday argument. We analyze in this note the intellectual background behind various misconceptions about Bayesian statistics, without aiming at a complete historical coverage of the reasons for this dismissal.