36-705 Intermediate Statistics

Instructor: Larry Wasserman
Time: MWF 12:30 - 1:20
Place: Baker Hall A51

Office Hour: Mondays 1:30 - 2:30 Baker Hall 132F

TA Information:
TA: Giuseppe Vinci (gvinci@andrew.cmu.edu)
Office hours: Tuesdays 3:00 - 4:00
Place: Baker Hall 132M

TA: Jisu Kim (jisuk1@andrew.cmu.edu)
Office hours: Thursdays 10:00 - 11:00
Place: Baker Hall 132M

TA: Daren Wang (darenw@andrew.cmu.edu)
Office hours: Wednesdays 3:00 - 4:00
Place: Baker Hall 132M

TA: Lawrence Wang (lawrencw@andrew.cmu.edu)
Office hours: Wednesdays 4:00 - 5:00
Place: Baker Hall 132M

Course 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 1 -- 12 from the text plus some supplementary material. This course is excellent preparation for advanced work in statistics and machine learning.

Textbook: Wasserman, L. (2004). All of Statistics: A concise course in statistical inference.


Other Recommended Texts:

Casella, G. and Berger, R. L. (2002). Statistical Inference, 2nd ed.
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 1-3 of of the book (basic probability) are familiar to you. If not you should take 36-700.

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.

Solutions


Lecture Notes

Download the notes and bring them to class.
Lecture Notes 1
Lecture Notes 2
Lecture Notes 3

Course Calendar
Week of: Mon Wed Thursday Friday
August 31 Review   Review, Inequalities   Homework 1   Inequalities
September 7 NO CLASS   Inequalities, O_P     VC Theory
September 14 Convergence Convergence Homework 2     Convergence
September 21 Convergence TEST I   Sufficiency
September 28 Likelihood Point Estimation Homework 3   Minimax Theory
October 5 Minimax Theory Asymptotics Homework 4   Asymptotics
October 12 Asymptotics Review   TEST II
October 19 Testing Testing Homework 5   MID-SEMESTER BREAK
October 26 Testing Confidence Intervals Homework 6   Confidence Intervals
November 2 Nonparametric Nonparametric Homework 7 Bootstrap
November 9 Bootstrap Bayesian Inference TEST III
November 16 Prediction Prediction Homework 8 Model Selection
November 23 NO CLASS NO CLASS
November 30 Model Selection Model Selection Homework 9   Regression
December 7 Causation Causation Homework 10   TBA