Undergraduate Probability Topics - MathOverflow most recent 30 from http://mathoverflow.net2013-05-18T21:47:32Zhttp://mathoverflow.net/feeds/question/37408http://www.creativecommons.org/licenses/by-nc/2.5/rdfhttp://mathoverflow.net/questions/37408/undergraduate-probability-topicsUndergraduate Probability TopicsJosh Guffin2010-09-01T18:10:21Z2011-03-04T04:55:02Z
<p>I am teaching undergraduate probability this semester, and I am looking for some suggestions about inspiring applications that could be reasonably covered over the course of two one-hour lectures or less. For example, here are two very cool topics I covered last time I taught this course:</p>
<ul>
<li>Search engines and Markov chains; <a href="http://www.ams.org/samplings/feature-column/fcarc-pagerank" rel="nofollow">AMS' description</a> and <a href="http://www.rose-hulman.edu/~bryan/google.html" rel="nofollow">The $25 billion eigenvector</a></li>
<li><a href="http://terrytao.wordpress.com/2009/07/03/benfords-law-zipfs-law-and-the-pareto-distribution/" rel="nofollow">Benford's Law and the Pareto Distribution</a></li>
</ul>
<p>Thanks in advance!</p>
http://mathoverflow.net/questions/37408/undergraduate-probability-topics/37415#37415Answer by Robert Bell for Undergraduate Probability TopicsRobert Bell2010-09-01T19:51:39Z2010-09-01T19:51:39Z<p>Here's a cool and accessible article by David Austin on percolation: <a href="http://www.ams.org/samplings/feature-column/fcarc-percolation" rel="nofollow">http://www.ams.org/samplings/feature-column/fcarc-percolation</a>. And if you do a quick Google search for "java percolation simulation" you will have access to quite a few nice in class demos.</p>
http://mathoverflow.net/questions/37408/undergraduate-probability-topics/37419#37419Answer by Bruno Stonek for Undergraduate Probability TopicsBruno Stonek2010-09-01T20:39:12Z2010-09-01T20:39:12Z<p>I think you might find this MO topic interesting: <a href="http://mathoverflow.net/questions/9218/probabilistic-proofs-of-analytic-facts" rel="nofollow">http://mathoverflow.net/questions/9218/probabilistic-proofs-of-analytic-facts</a> , especially Bernstein's proof of the Weierstrass theorem.</p>
http://mathoverflow.net/questions/37408/undergraduate-probability-topics/37421#37421Answer by Joseph O'Rourke for Undergraduate Probability TopicsJoseph O'Rourke2010-09-01T20:42:12Z2010-09-01T20:42:12Z<p>Kenneth Levasseur's paper, "How to Beat Your Kids at Their Own Game"
analyzes the simple game of guessing whether the next card in a deck is red or black.
He computes the expected score of correct guesses if you count carefully.
There is a nice geometric flavor to his analysis.
With the standard 52-card deck, the expected score is slightly over 30.</p>
<p><a href="http://www.jstor.org/stable/2689550" rel="nofollow"><em>Mathematics Magazine</em> Vol. 61, No. 5 (Dec., 1988), pp. 301-305.</a></p>
http://mathoverflow.net/questions/37408/undergraduate-probability-topics/37479#37479Answer by Keivan Karai for Undergraduate Probability TopicsKeivan Karai2010-09-02T09:41:40Z2010-09-02T09:41:40Z<p>One topic with a lot of "applications" is the so-called secretary problem.
<a href="http://en.wikipedia.org/wiki/Secretary_problem" rel="nofollow">http://en.wikipedia.org/wiki/Secretary_problem</a></p>
<p>You can use it as an example to introduce them to the concept of stopping time. There is a lot of variations of the problem (say, replace finding the best by maximizing the expected value) that allow them to explore different aspects of the theory.</p>
http://mathoverflow.net/questions/37408/undergraduate-probability-topics/37494#37494Answer by Jon Peterson for Undergraduate Probability TopicsJon Peterson2010-09-02T13:05:52Z2010-09-02T13:05:52Z<p>If you talk about Markov chains at some point there are a lot of cool applications to baseball. For instance using available batting statistics you can construct a team consisting of 9 Alex Rodriguez's and compute (or simulate really) how many runs such a team would score in 9 innings. You can do more detailed analysis of players as well. One place to look for more details about this (and other fun applications in sports) is the book "Mathletics" by Wayne Winston.</p>
<p><a href="http://www.amazon.com/Mathletics-Gamblers-Enthusiasts-Mathematics-Basketball/dp/069113913X/ref=sr_1_1?ie=UTF8&s=books&qid=1283432632&sr=8-1" rel="nofollow">http://www.amazon.com/Mathletics-Gamblers-Enthusiasts-Mathematics-Basketball/dp/069113913X/ref=sr_1_1?ie=UTF8&s=books&qid=1283432632&sr=8-1</a></p>
http://mathoverflow.net/questions/37408/undergraduate-probability-topics/37507#37507Answer by Roberto Imbuzeiro Oliveira for Undergraduate Probability TopicsRoberto Imbuzeiro Oliveira2010-09-02T15:08:44Z2010-09-02T15:08:44Z<p>Here is another suggestion involving Markov chains: Example 1 in Diaconis' <a href="http://www.ams.org/journals/bull/2009-46-02/S0273-0979-08-01238-X/home.html" rel="nofollow">The Markov Chain Monte Carlo revolution</a>. This is a very surprising application of MCMC to decoding messages exchanged between interns in California's prision system. </p>
http://mathoverflow.net/questions/37408/undergraduate-probability-topics/57314#57314Answer by Joel Reyes Noche for Undergraduate Probability TopicsJoel Reyes Noche2011-03-04T03:23:21Z2011-03-04T03:23:21Z<p>For an application involving game theory, try <a href="http://en.wikipedia.org/wiki/Parrondo%27s_paradox" rel="nofollow">Parrondo's Paradox</a>: "Given two games, each with a higher probability of losing than winning, it is possible to construct a winning strategy by playing the games alternately."</p>
http://mathoverflow.net/questions/37408/undergraduate-probability-topics/57317#57317Answer by Matthew Kahle for Undergraduate Probability TopicsMatthew Kahle2011-03-04T04:55:02Z2011-03-04T04:55:02Z<p>The Bayer and Diaconis paper, "Trailing the Dovetail Shuffle to its Lair" is a classic and Brad Mann gave a <a href="http://www.dartmouth.edu/~chance/teaching_aids/Mann.pdf" rel="nofollow">very readable exposition</a> of it.</p>
<p>Many people have heard, "seven shuffles are necessary to mix up a deck of cards." But it is great for undergraduates to learn what exactly is meant mathematically by <em>shuffle</em>, and especially what is meant by <em>mix up</em>.</p>