Discovery, Winter, 2010-2011


Course Number: 4040-820-01
Time: TuTh / 12-1:50 PM
Room:70-1610
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:
DateTopicReadingHomework
Tuesday, Nov. 30ProbabilityChapter 1 Prove Bayes' Theorem (strong version) + Chapter 1, problems 5, 10, 11, 12, 13, 15, 19, 20 (Due Friday, Dec. 2)
Thursday, Dec. 2Random Variables2.1, 2.2, 2.3 on Bernoulli, 2.4 on Normal, 2.5, 2.6Chapter 2, problems 4, 5, 10, 11(a), 14, 20 (Due Tuesday, Dec. 14)
Monday, Dec. 6 8:00am - 9:50am in 78-2015
note special time/location!
Finish Random Variables, Expectations, Variance, Covariance, Markov's Inequality2.7, 2.8, 2.9, 3.1, 3.2, 3.3, 3.5, 4.1
Tuesday, Dec. 7
(no class!)
Thursday, Dec. 9Matlab Tutorial
Tuesday, Dec. 14Hoeffding's Inequality4.1 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. 16Point Estimation, Confidence IntervalsChapter 6Chapter 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. 6Overview of Machine Learning
Tuesday, Jan. 11Student Presentations on Statistics 1: Emma, Sam, Nishant (see below)
Thursday, Jan. 13Student 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)
  • Log-Linear 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)