10-705/36-705 Intermediate Statistics
Last Year's Final Exam
Final Exam: Friday Dec 14 5:30 - 8:30
Instructor: Larry Wasserman
Time: MWF 12:30 - 1:20
Place: GHC 4307Office Hour: Mondays 1:30 - 2:30 Baker Hall 228a
TA: Wanjie Wang (wwang@stat.cmu.edu) Office hours: Tuesdays 4:00-5:00
Place: FMS 320TA: Haijie (Jay) Gu (haijieg@cs.cmu.edu) Office hours: Wednesdays 3:30-4:30
Place: GHC 8008Course Assistant: Mari-Alice McShane mcshane@stat.cmu.edu Office: Baker Hall 229K
Course description
This course will cover the fundamentals of theoretical statistics. We will cover Chapters 5 -- 10 from Casella and Berger plus a lot of supplementary material. This course is excellent preparation for advanced work in statistics and machine learning.Textbook: Casella, G. and Berger, R. L. (2002). Statistical Inference, 2nd ed.
Other Recommended Texts:
Wasserman, L. (2004). All of Statistics: A concise course in statistical inference.
Bickel, P. J. and Doksum, K. A. (1977). Mathematical Statistics.
Rice, J. A. (1977). Mathematical Statistics and Data Analysis, Second Edition.
Prerequisites
I assume that you know the material in Chapters 1-4 of Casella and Berger (basic probability theory).The syllabus includes information about assignments, exams and grading.
Assignments
Assignments are due on Thursdays at 3:00 p.m. Hand in the assignment to Mari-Alice McShane in Baker Hall 229K.
You can also email them to her. Send a PDF file to: mcshane@stat.cmu.edu. Make sure you put "Stat 705 Assigment" in the subject line.
Homework 1 due Thurs Sept 6 by 3:00 Homework 2 due Thurs Sept 20 by 3:00 Homework 3 due Thurs Sept 27 by 3:00 Homework 4 due Thurs Oct 4. Warning! Long homework: by 3:00 Homework 5 due Thurs Oct 18 by 3:00 Homework 6 due Thurs Oct 25 by 3:00 Homework 7 due Thurs Nov 1 by 3:00 Homework 8 due Thurs Nov 15 by 3:00 Homework 9 due Thurs Nov 29 by 3:00
Solutions
Homework 1 Solutions Homework 2 Solutions Homework 3 Solutions Homework 4 Solutions Homework 5 Solutions Homework 6 Solutions Homework 7 Solutions Homework 8 Solutions Homework 9 Solutions
Test1 1 Solutions Test1 2 Solutions Test1 3 Solutions
Lecture Notes
Download the notes and bring them to class.
Lecture Notes 1 Lecture Notes 2 Lecture Notes 3 Lecture Notes 4 Lecture Notes 5 Lecture Notes 6 Lecture Notes 7 Lecture Notes 8 Lecture Notes 9 Lecture Notes 10 Lecture Notes 11 Lecture Notes 12 Lecture Notes 13 Lecture Notes 14 Lecture Notes 15 Lecture Notes 16 Lecture Notes 17Course Calendar
Week of: Mon Wed Thursday Friday August 27 Review Review, Inequalities Inequalities September 3 NO CLASS Inequalities, O_P Homework 1 VC Theory September 10 Convergence Convergence Test I September 17 Convergence Convergence Homework 2 Sufficiency September 24 Likelihood Point Estimation Homework 3 Minimax Theory October 1 Minimax Theory Asymptotics Homework 4 Asymptotics October 8 Asymptotics Review Test II October 15 Testing Testing Homework 5 MID-SEMESTER BREAK October 22 Testing Testing Homework 6 Confidence Intervals October 29 Nonparametric Nonparametric Homework 7 Bootstrap November 5 Bootstrap Review Test III November 12 Bayesian Inference Bayesian Inference Homework 8 Bayesian Inference November 19 NO CLASS NO CLASS NO CLASS November 26 Prediction Prediction Homework 9 Model Selection December 3 Model Selection Causation Causation