Wiki page for the Theory of Probability (STATS 116) class in summer 2012.
SyllabusEdit
The material covered in the course was guided by Sheldon Ross's textbook, A First Course in Probability. Chapters 16 were covered in detail, and portions of chapters 78 were discussed in the last few weeks of the course. These chapters cover basic combinatorics, axioms of probability, conditional probability, random variables (discrete and continuous), joint distributions, expected value, and limit theorems.
Material on final examEdit
Professor Siegmund emphasized the importance of a conceptual understanding of the material covered over specific distributions and solutions. However, he gave an outline of the distributions students should be familiar with on the last day of class and the important concepts.
Distributions that may be on the examEdit
 Binomial
 Normal
 Poisson
 Geometric
 Negative Binomial
 Hypergeometric
 Multinomial
 perhaps Beta
 Bivariate Normal
Important concepts/formulasEdit

 the term drops out when the X's are independent random variables
 , also known as the Wikipedia:Law of total expectation
 . known as the Wikipedia:law of total variance
 momentgenerating functions and generating functions
 joint density functions
 limit theorems (law of large numbers and central limit theorem)
External linksEdit
 coursework is where most information is stored about the course.