removed stat stuff; most people don't do that, so it looks less overw…

…helming with a shorter list.

general-resources/courses.md

@@ -163,58 +163,5 @@ this course, since there is a fair amount of overlap, with the graduate course
 focusing more on understanding the method and the undergraduate course more on
 using FEM software (COMSOL) for a larger variety of applications.
 
-
-## Statistics for Monte Carlo (Math)
-- C281A: Probability Theory
-The course is designed as a sequence with Statistics C205B/Mathematics C218B
-with the following combined syllabus. Measure theory concepts needed for
-probability. Expection, distributions. Laws of large numbers and central limit
-theorems for independent random variables. Characteristic function methods.
-Conditional expectations, martingales and martingale convergence theorems.
-Markov chains. Stationary processes. Brownian motion. Also listed as Statistics
-C205A.
-
-- C223A/B: Advanced Topics in Probability and Stochastic Processes
-The topics of this course change each semester, and multiple sections may be
-offered. Advanced topics in probabilty offered according to students demand and
-faculty availability. Also listed as Statistics C206A.
-
-
-## Statistics (stat)
-
-### Probably Useful
-+ 150: Stochastic Processes
-Random walks, discrete time Markov chains, Poisson processes. Further topics
-such as: continuous time Markov chains, queueing theory, point processes,
-branching processes, renewal theory, stationary processes, Gaussian processes.
-
-+ 157: Seminar on Topics in Probability and Statistics: Reproducible and
-Collaborative Data Science
-Substantial student participation required. The topics to be covered each
-semester that the course may be offered will be announced by the middle of the
-preceding semester; see departmental bulletins. Recent topics include: Bayesian
-statistics, statistics and finance, random matrix theory, high-dimensional
-statistics.
-
-### Possibly Useful
-- 20: Introduction to Probability and Statistics
-For students with mathematical background who wish to acquire basic concepts.
-Relative frequencies, discrete probability, random variables, expectation.
-Testing hypotheses. Estimation. Illustrations from various fields.
-
-- 134: Concepts of Probability
-An introduction to probability, emphasizing concepts and applications.
-Conditional expectation, independence, laws of large numbers. Discrete and
-continuous random variables. Central limit theorem. Selected topics such as the
-Poisson process, Markov chains, characteristic functions.
-
-- C206B: Advanced Topics in Probability and Stochastic Processes
-We will cover a range of topics in modern discrete probability structured
-around 3-5 week modules on some of the following topics (percolation, random
-graphs, mixing times/Markov chains, spin systems, concentration
-inequalities/large deviations, random walks in random environments, random
-constrain satisfaction problems) - the exact choice will depend on student
-interests.
-
 ## Writing
 - GSPDP 320