10-705/36-705 Intermediate Statistics
Instructor: Larry Wasserman
Time: MWF 12:30 - 1:20
Place: Scaife 125Office Hour: Mondays 1:30 - 2:30 Baker Hall 228a
Announcements:
(updated Dec 1)Final Exam: Monday December 12, 8:30-11:30 a.m., DH 1212
PRACTICE EXAM
End of Announcements
TA: Wanjie Wang (wwang@stat.cmu.edu) Office hours: Tuesdays 4:30-5:30
Place: FMS 320TA: Xiaolin Yang (xyang@stat.cmu.edu) Office hours: Wednesdays 3:00-4:00
Place: FMS 320TA: Liang Xiong (excelly@gmail.com) Office hours: Thursdays 10:00 - 11:00 a.m.
Place: FMS 320Course 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 some 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 8 by 3:00 Homework 2 due Thurs Sept 15 by 3:00 Homework 3 due Thurs Sept 22 by 3:00 Homework 4 due Thurs Sept 29 by 3:00 Homework 5 due Thurs Sept 29 by 3:00 WARNING: Long homework Homework 6 due Thurs Oct 20 by 3:00 Homework 7 due Thurs Oct 27 by 3:00 Homework 8 due Thurs Nov 10 by 3:00 Homework 9 due Thurs Nov 17 by 3:00 Homework 10 due Thurs Dec 1 by 3:00
Solutions
Homework 1 SOLUTIONS Homework 2 SOLUTIONS Homework 3 SOLUTIONS SOLUTIONS for Test 1 Homework 4 SOLUTIONS Homework 5 SOLUTIONS Homework 6 SOLUTIONS Test 2 SOLUTIONS Homework 7 SOLUTIONS Homework 8 SOLUTIONS Test 3 SOLUTIONS Homework 9 SOLUTIONS Homework 10 SOLUTIONS
Lecture Notes
Download the notes and bring them to class.
Lecture Notes 1 Lecture Notes 2 Lecture Notes 3 Lecture Notes 4 Addendum to Lecture Notes 4 Lecture Notes 5 Lecture Notes 6 Lecture Notes 7 Lecture Notes 8 SUMMARY OF MINIMAX THEORY 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 17
Course Calendar
Week of: Mon Wed Thursday Friday August 29 Review Review, Inequalities Inequalities September 5 NO CLASS Inequalities, O_P Homework 1 VC Theory September 12 Convergence Convergence Homework 2 Test I September 19 Convergence Sufficiency Homework 3 Sufficiency September 26 Point Estimation Point Estimation Homework 4 Minimax Theory October 3 Minimax Theory Asymptotics Homework 5 Asymptotics October 10 Asymptotics Review Test II October 17 Testing Testing Homework 6 MID-SEMESTER BREAK October 24 Testing Confidence Intervals Homework 7 Confidence Intervals October 31 Nonparametric Nonparametric Review November 7 Test III No Class Homework 8 The Bootstrap November 14 The Bootstrap Bayesian Inference Homework 9 Bayesian Inference November 21 NO CLASS NO CLASS NO CLASS November 28 Prediction Prediction Homework 10 Model Selection December 5 30 Model Selection Causation Review