Statistics 610a, Fall 2001
Statistical Inference

A systematic development of the mathematical theory of statistical inference covering methods of estimation, hypothesis testing, and confidence intervals. An introduction to statistical decision theory. Undergraduate probability at the level of Statistics 241a assumed.
Instructor:David Pollard
Office hours:Wednesday 3:00 - 4:00, or by appointment
Time:Monday, Wednesday 1:00 - 2:20
Place:24 Hillhouse
TA:Peter Radchenko

Aim of the course

I hope that students who complete the course will be able to read some of the current statistical or econometrics literature, or at least understand the the standard theory behind those literatures. The course covers a range of topics similar to Statistics 242 (with the exception of the theory of linear models, which is covered in Statistics 612a), but the treatment will be more rigorous. In particular, the course will put more emphasis on the decision-theoretic interpretation of statistical procedures.

An understanding of statistical theory at the level of this course is necessary background for many of the more advanced courses offered by the Statistics Department.


As with all my graduate courses, there will be no exams. The final grade will be based completely on the homework assignments. I expect to hand out about ten assignments during the course. Details of my grading system will be explained in the first class.

Texts and references

In the past I have worked from a number of books, none of which I have found completely satisfactory. For the current course, I intend to borrow from several sources, as described in the reference list. For some topics, I will provide notes specifically written for this class.


30 Sept2001