You are currently browsing the tag archive for the ‘Events’ tag.

Today I came across an interesting question on the mathoverflow: what are the biggest problems in probability theory? In the answers, there is one about self-avoiding walks. And the most famous scientist in this field, as far as I know, is Gordon Slade. And several days ago, I also saw a post of this subject. At that time, I have no idea about this area, so I did not have anything feeling about this and then I just skipped it. Now I think I have realized the importance of this field in the whole probability theory. Thus I have to know something about this, at least getting to know what it is. Here I want to share you with the materials I have collected.

http://chromotopy.org/?p=402 (a recent post about the talk given by Professor Slade)

http://gowers.wordpress.com/2010/08/22/icm2010-smirnov-laudatio/ (a post about this area)

http://terrytao.wordpress.com/2010/08/19/lindenstrauss-ngo-smirnov-villani/ (a post about the winners in icm2010, including this area)

http://www.springer.com/librarians/e-content/ebooks?SGWID=0-40791-12-784104-0

The Elements of Statistical Learning 

9780387848570_230x153

Numerical Optimization 

0387303030_210x153

A Modern Introduction to Probability and Statistics 

1852338962_237x153

Time Series Analysis -With Applications in R

9780387759586_214x153

Applied Statistics Using SPSS, STATISTICA, MATLAB and R 

9783540719717_231x153 

An Introduction to Programming and Numerical Methods in MATLAB 

1852339195_202x153

Graph Theory 

9781846289699_245x153

Lattice -Multivariate Data Visualization with R

9780387759685_232x153

The Concise Encyclopedia of Statistics 

9780387317427_222x153 

Handbook of Financial Time Series 

9783540712961_218x153

Asymptotic Theory of Statistics and Probability 

9780387759708_246x153

An Introduction to Ordinary Differential Equations 

9780387712758_232x153

Data Manipulation with R 

9780387747309_231x153 

Ordinary and Partial Differential Equations 

9780387791456_231x153

Bayesian Computation with R 

9780387922973_231x153 

I have noticed this concept before. Since I am just new in Probability field, so you should forgive me that I just noticed this academic area several months ago and did not realize the importance of it. Today I attended the regular colloquium of my department and the speaker, Zbigniew J. Jurek, gave a lecture about The Random Integral Representation Conjecture. In this talk, he mentioned free probability. Moreover, he also joked that free statistics will come into being.

I also fount a useful link about the survey of free probability. I hope it will be useful for you. Terry Tao also have a post about this.

General philosophy of probability theory
Probability is central to science, more than any other part of math. It enters statistics, physics, biology, and even medicine as we will see when and if we discuss tomography. This is the broad view.
There is also a narrow view – one needs to understand it before one can effectively apply it and it has many subtleties. Possibly this is due to the fact that probability, stochasticity, or randomness, may not actually exist! I think it mostly exists in our uncertainty about the world. The real world seems to be deterministic (of course one can never test this hypothesis). It is chaotic and one uses probabilistic models to study it mainly because we don’t know the initial conditions. Einstein said that ”god does not play dice”. My own view is that the world may be deterministic, but I like to think I have free will. I believe that probability should be regarded only as a model of reality.

From the notes of Lawrence A. Shepp

Recent Comments

Tomáš on 【Bio-Glossary】Biological Repli…

Blog Stats

  • 90,872 hits

Enter your email address to subscribe to this blog and receive notifications of new posts by email.

Join 525 other followers

Twitter Updates

Error: Twitter did not respond. Please wait a few minutes and refresh this page.