Statistics is Easy

Dennis Shasha
Courant Institute of Mathematical Sciences, New York University
Inria, Zenith team, Montpellier
Friday, March 6 2015, 2pm, IBC (LIRMM Bat 5) room 02/22 (see map)

Few people remember statistics with much love. To some, probability was fun because it felt combinatorial and logical (with potentially profitable applications to gambling), but statistics was a bunch of complicated formulas with counter-intuitive assumptions. As a result, if a practicing natural or social scientist must conduct an experiment, he or she can't derive anything from first principles but instead pulls out some dusty statistics book and applies some formula or uses some software, hoping that the distribution assumptions allowing the use of that formula apply. To mimic a familiar phrase: "There are hacks, damn hacks, and there are statistics."

Surprisingly, a strong minority current of modern statistical theory offers the possibility of avoiding both the magic and the assumptions of classical statistical theory through randomization techniques known collectively as resampling. These techniques take a given sample and either create new samples by randomly selecting values from the given sample with replacement or by randomly shuffling labels on the data. The questions answered are the familiar: how accurate is my measurement likely to be (confidence interval) and could it have happened by mistake (significance).

This talk explains the basic of resampling statistics through a number of simple-to-understand examples such as tossing coins,
evaluating the effectiveness of drugs, and determining the sane reaction to a medical test result.

The talk will be in French but the power points will be in English.

It would be good if the participants could get the book before the lecture (should be freely downloadable if your library has an account at Morgan Claypool ):
Statistics is Easy!
Dennis Shasha and Manda Wilson
Synthesis Lectures on Mathematics and Statistics, Morgan Claypool
http://www.morganclaypool.com/doi/abs/10.2200/S00142ED1V01Y200807MAS001


Bio :
Dennis Shasha is a professor of computer science at the Courant Institute of Mathematical Sciences, a division of New York University. His current areas of research include work done with biologists on pattern discovery for microarrays, combinatorial design, network inference, and protein docking; work done with physicists, musicians, and professionals in finance on algorithms for time series; and work on database applications in untrusted environments. Other areas of interest include database tuning as well as tree and graph matching.

After graduating from Yale in 1977, he worked for IBM designing circuits and microcode for the IBM 3090. While at IBM, he earned his M.Sc. from Syracuse University in 1980. He completed his Ph.D. in applied mathematics at Harvard in 1984.

Professor Shasha has written six books of puzzles, five of which center on the work of a mathematical detective by the name of Jacob Ecco, a biography about great computer scientists and several technical books relating to his various areas of research (biological computing, databases, statistics, etc.).  He has written monthly puzzle columns for Scientific American and Dr. Dobb's Journal. In 2013 he became a fellow of the Association for Computing Machinery.

Dennis Shasha is member of the Scientific Comitee of "Institut de Biologie Computationnelle" (IBC)

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