Statistics 242b

Statistical Inference (Statistics 242/542) Spring 1996

Instructor: David Pollard (;
Office: Statistics Department, 24 Hillhouse Avenue. Phone: 432-0666
Office hours: Monday 12:00--2:00

Teaching Assistant: Alex Thiry (
Office hours: Please email to arrange office hours

Prerequisites: Statistics 241a and linear algebra, at the level of Math 220.

Problem set about every two weeks, counting for 40% of final grade
Midterm test, counting for a token 10% of final grade
Final exam, counting for 50% of final grade

Homework policy:
Late homework accepted only with a Dean's note. No work accepted after distribution of solution sheet.

Aim of the course

"Principles of statistical analysis: maximum likelihood, sampling distributions, estimation, confidence intervals, tests of significance, regression, analysis of variance, and the method of least squares."

Text: Rice "Mathematical Statistics and Data Analysis"

I hope to cover most of the material in Chapters 7 to 12, and 14, of Rice, with some material from Chapters 13 and 15 if time permits. I would expect to devote about the same amount of time to each topic as I did when I last used the Rice text, in 1990, but with some modifications to allow for more discussion of computing issues. I strongly recommend that students who take 242 also enrol in Statistics 200b.

Click Very little technical material, but good for discussion of subtle ideas. Fun to read.]

  • Bickel and Doksum "Mathematical Statistics: Basic Ideas and Selected Topics" (Holden-Day, 1977) [ A text at the next level up from 242. A good source for more detailed information.]

  • Chambers, Cleveland, Kleiner, and Tukey "Graphical Methods for Data Analysis" (Wadsworth, 1983) [ Good discussion of topics such as Q-Q plots.]

  • Tanur, Mosteller, Kruskal, Link, Pieters, and Rising "Statistics: A Guide to the Unknown" (Holden-Day, 1972). [A collection of short articles that illustrate many aspects of statistics. I might steal from it.]

  • Stuart "Basic Ideas of Scientific Sampling" (Griffin, 1968). [Good discussion of sampling, with lots of simple numerical examples.]

    Material covered in 1990

    Here is the breakdown of the course for Spring 1990. I intend to follow the same order of topics this year, but with some reapportionment of time spent on each chapter.

    Survey sampling (Chapter 7; Lectures 1-6)

    Estimation (Chapter 8; Lectures 7-11) Hypothesis testing and goodness-of-fit (Chapter 9; Lectures 12-17) There was some overlap between the last topic for Chapter 9 and the topics for Chapter 10.

    Summarizing data (Chapter 10; Lectures 18-20)

    Comparing two samples (Chapter 11; Lectures 21-24) Analysis of variance (Chapter 12; Lectures 25-30) Regression (Chapter 14; Lectures 31-34) Decision theory and Bayesian inference (Chapter 15; Lectures 35-36)