Demography 211, Spring 2004

Advanced Demographic Analysis

Demography 211
UC Berkeley, Spring 2008
Prof. John R. Wilmoth

OVERVIEW

This course is designed to provide an overview of quantitative techniques commonly used in demography, sociology, economics, and other social sciences. Methods are described carefully in both words and formulas, and students are encouraged to learn to move freely between verbal and mathematical representations of data. Weekly homework exercises teach and reinforce basic concepts.

Some exercises are computer-based and assume knowledge of R, although arrangements can be made for students who lack experience with this particular statistical programming language. Some knowledge of calculus is helpful but not required. Student backgrounds (in mathematics, statistics, and computer skills) are typically quite diverse, and accommodation of this diversity is a perennial challenge for the instructor!

The syllabus provides a detailed description of course content.

TEXTBOOKS FOR THE COURSE

As shown on the syllabus, readings from various sources will be used for this class. The following two textbooks will be used extensively during several weeks of the course:

(1) Jay L. Devore, Probability and Statistics for Engineering and the Sciences (5^th ed.), Duxbury Press, Pacific Grove, CA, 1999.

(2) Daniel A. Powers and Yu Xie, Statistical Methods for Categorical Data Analysis, Academic Press, 2000.

These two books are highly recommended, and students should consider purchasing one or both of them, either from the ASUC bookstore or by some other means. Both books will also be held on reserve in the Demography library. Despite the cost these are useful texts, and you should have your own copies, if possible.

REFERENCE FOR R

(3) W.N. Venables, D.M. Smith, and the R Development Core Team. An Introduction to R. Version 2.5.1 (2007-06-27).

(4) S-Plus 5 for Unix Guide to Statistics, Data Analysis Products Division, Mathsoft, Seattle, 1998. (chapters 1-16, chapters 17-33)

OTHER READINGS

Students may gain access to electronic versions of other course readings by clicking here.

LECTURE NOTES, HANDOUTS, AND HOMEWORK ASSIGNMENTS

In general, homework assignments will be distributed in class (and posted online) on the second day that a given topic is presented in lecture; they are due, in most cases, on the day when the next homework assignment is scheduled for distribution.* The instructor is also posting his lecture notes and handouts here (with some delay) as an aid to students in the class. Access to all of these documents requires a password, which will be provided during lecture and is for use only by students who are enrolled in the class (or by approved auditors).

Some homework assignments refer to data files that available through the following link: Data.

Topic	Dates topic is covered in class	Lecture notes	Handouts	Homework assignment	Date HW distributed	Date HW due
Summary measures	Jan 22, 24, 29	Lec 1	Hand 1	HW 1	Jan 22	Feb 4
Graphical methods	Jan 31, Feb 5, 7	Lec 2		HW 2	Jan 31	Feb 11
Probability	Feb 7, 12, 14	Lec 3		HW 3	Feb 7	Feb 19
Sampling	Feb 19, 21	Lec 4		HW 4	Feb 19	Feb 26
Estimation	Feb 26, 28, Mar 4, 6	Lec 5	Hand 5	HW 5	Feb 26	Mar 4
Hypothesis testing	Mar 11, 13, 18	Lec 6		HW 6	Mar 4	Mar 13
Two-way tables	Apr 1, 3, 8	Lec 7	Two-way 1 Two-way 2	HW 7	Apr 1	Apr 11
Regression	Apr 8, 14, 15, 22, 24	Lec 8		HW 8 HW 9	Apr 8 Apr 22	Apr 15 Apr 29
Generalized linear models	Apr 29, May 1, 6,8	Lec 9	Poisson vs. Binomial Chap 2 - R code Chap 3 - R code	HW 10	Apr 29	May 12