Discovery, Winter, 20102011
Course Number: 404082001
Time: TuTh / 121:50 PM
Room:701610
Website: people.rit.edu/~jcdicsa/courses/Discovery/
Instructors: Justin Domke and Linwei Wang
Course Text: All of Statistics, by Wasserman and Advanced Linear Algebra for Engineers with MATLAB, by Dianat and Saber.
Grading Scheme:
 15% Homework
 10% Participation
 45% Presentations
 30% Final
Lectures:
Date  Topic  Reading  Homework 
Tuesday, Nov. 30  Probability  Chapter 1 
Prove Bayes' Theorem (strong version) +
Chapter 1, problems 5, 10, 11, 12, 13, 15, 19, 20 (Due Friday, Dec. 2)

Thursday, Dec. 2  Random Variables  2.1, 2.2, 2.3 on Bernoulli, 2.4 on Normal, 2.5, 2.6  Chapter 2, problems 4, 5, 10, 11(a), 14, 20 (Due Tuesday, Dec. 14) 
Monday, Dec. 6 8:00am  9:50am in 782015 note special time/location!  Finish Random Variables, Expectations, Variance, Covariance, Markov's Inequality  2.7, 2.8, 2.9, 3.1, 3.2, 3.3, 3.5, 4.1  
Tuesday, Dec. 7  (no class!) 
Thursday, Dec. 9  Matlab Tutorial   
Tuesday, Dec. 14  Hoeffding's Inequality  4.1  Prove V(X)=E[X^2](E[X])^2. + Chapter 3, problems 1, 3, 5, 6, 13, 21 (Due Friday Dec. 17 6pm) 
Thursday, Dec. 16  Point Estimation, Confidence Intervals  Chapter 6  Chapter 6, problems 1, 2, 3 (Due Jan 4, 2011) 
(break) 
Tuesday, Jan. 4  (Last Statistics
Lecture)   Chapter 10, problems 7(b), and 8. (Due
Jan. 11) 
Thursday, Jan. 6  Overview of Machine Learning   
Tuesday, Jan. 11  Student Presentations on Statistics
1: Emma, Sam, Nishant (see below)   
Thursday, Jan. 13  Student Presentations on Statistics
2: Abdul, Azar, Ricardo, Lei (see below)   
Tuesday, Jan. 18  (Begin Linear Algebra Section)   
Final Exam: Tuesday Feb. 22, 2011, 12:30pm  2:30pm (Location TBD)
Student Presentation Options for Statistics
 Convergence of Random Variables (5.1, 5.2, 5.3, 5.4) (Emma)
 Cross Validation (Azar)
 The Bootstrap (Chapter 8)
 Statistical Decision Theory (12.1, 12.2, 12.3, 12.4, 12.6)
 Linear and Logistic Regression. (13.1, 13.2, 13.3, 13.4,
13.7) (Ricardo)
 Directed Graphs (Chapter 17) (Abdul)
Undirected Graphs (Chapter 18) (Nishant)
 LogLinear Models (Chapter 19)
 Smoothing Using Orthogonal Functions (21.1, 21.2, 21.3, 21.4)
 Classification (Chapter 22) (Lei)
 Statistical Modeling: The Two Cultures, Leo Breiman, Statistical
Science 2001, Vol. 16, No. 3. You should also cover the commentary
that comes after the paper. (Sam)
