- Thursday, April 28, 2016
- 3:40 PM–4:30 PM
- North Hall 276
Joshua Ruiter and David Zhang
Lie algebras (and Lie groups) are important for many applications, including models in quantum physics, but Lie algebras and their classification have since grown to be subject worthy of study from a pure algebraic perspective. By working with the concrete example of 3x3 matrices with trace zero, we'll see instances of many important concepts in the study of Lie algebras, including bilinearity, subalgebras and ideals, simultaneous diagonalization of linear maps, and root systems.
There are two major schools of thoughts in statistics: the frequentist and the Bayesian. Frequentist statisticians asks for the probability of the observed data given a certain distribution parameter, while Bayesian statistcians asks for the probability of a distribution parameter given a certain observed data. Moreover, the frequentist method relies on experimental results alone, while the Bayesian method relies on experimental results combined with past experience. This difference in philosophy leads not only to a difference in statistical inferences but also to a difference in our view of reality and science. In this presentation, I will compare the two schools of thoughts in statistics and use simple examples to illustrate the differences. I will also present my analysis of professional golf players’ putting performance using the Bayesian method.
Refreshments precede these talks in NH-282 at 3:30pm.