Professor Rebecca Jean Emigh
Soc. 210B. Intermediate Statistical Methods
Time: Lecture: Tuesdays and Thursdays, 2:00 to 3:30, Hershey 1655
Lab: Thursdays, 12:00 to 1:45, Public Policy 2035H (SSC Computing Lab.).
email: emigh@bigstar.sscnet.ucla.edu
Office: Hershey 2310
Office Hours: Tuesdays, 3:30 to 5:00.
TA: Shige Song
 

Course Description:

This is the second half of the required statistics sequence for graduate students in sociology.
The class meets twice a week for lecture and once a week for a lab. In class, we go through the theory of the statistical methods. We will also do occasional exercises and discussions in class. The lab is run by the TA. It is a chance for hands-on practice with the statistical package.
 

Course requirements:

The requirements for the class consist of five short papers (5 pages each). They are due every other week. You will be given a data set to analyze and you will have to produce the appropriate tables and graphs and then write up the analysis. It takes a long time to complete the papers; if you start the night before, I guarantee you will fail. The due dates are on the syllabus. There are no exams. All papers and summaries should be turned in as indicated, either in class (always at the beginning of the class) or to my mailbox. Please do not bring them to my office.

Other general bits of information:

Grades: Your grade is based on your papers. I believe strongly in improvement and will factor this into account when assigning final grades.

Getting the readings: I ordered the Allison, Fox, Berry, Hardy, Mohr, Jaccard et al., and Rabe-Hesketh and Everitt at ASUCLA. Also, there is a very small reader with the materials for the discussions at Westwood Copies, 1001 Gayley in Westwood Village, 310-208-3233. It will be ready in time for the discussions.

Finding me: It is easiest to get a hold of me by email; I check it all the time when I am in my office. I do not have an answering machine, so telephoning me is not terribly useful. Please try to come to office hours if you have questions, but if this is impossible, we can make an appointment. I am a very reliable, dependable person. It is not difficult to locate me.

We will have a web page for the course and lecture notes will be posted there, along with some of the data sets for the class.

I DO NOT ACCEPT LATE PAPERS NOR DO I GIVE INCOMPLETES!

Books:

Fox, John. 1997. Applied Regression Analysis, Linear Models, and Related Methods. Thousand Oaks, CA: Sage.

Allison, Paul D. 1999. Multiple Regression. Thousand Oaks, CA: Pine Forge Press.

Rabe-Hesketh, Sophia and Brian Everitt. 1999. A Handbook of Statistical Analyses Using Stata. Boca Raton, FL: Chapman & Hall. (Note: This is reading for the papers, not for class. I’ll give page numbers for this text on the handouts for the papers.)

Jaccard, James; Robert Turrisi, and Choi K. Wan. 1990. Interaction Effects in Multiple Regression. Newbury Park, CA: Sage.

Berry, William D. 1993. Understanding Regression Assumptions. Newbury Park, CA: Sage.

Hardy, Melissa A. 1993. Regression with Dummy Variables. Newbury Park, CA: Sage.

Mohr, Lawrence B. 1990. Understanding Significance Testing. Newbury Park, CA: Sage.
 
 

Schedule of Topics and Readings
 

Week 1. Bivariate Regression.

Session 1. Tuesday, January 9th: Bivariate Relationships, Tables, Plots.
Fox, pp. 3-58
Allison, pp. 1-48
Paper 1 handed out.

Session 2. Thursday, January 11th : Bivariate Regression.
Fox, pp. 85-97
Allison, pp. 97-117
 

Week 2.

Session 3. Tuesday, January 16th : Correlation
 

Session 4. Thursday, January 19th: Review of Significance Testing
Mohr, pp. 7-74 (read for review)
 

Week 3. Multiple Regression.

Session 5. Tuesday, January 23rd: Inference for Regression.
Paper 1 due in class, at the beginning of class. Paper 2 handed out.
Fox, pp. 112-119

Session 6. Thursday, January 25th: Multiple Regression
Fox, pp. 97-111
 

Week 4.

Session 7.  Tuesday, January 30th: Inference for Multiple Regression
Fox, pp. 120-134

Session 8. Thursday, February 1st: Discussion of Causality
Marini and Singer, “Causality in the Social Sciences” and Pearl, “The
Art and Science of Cause and Effect.”
 

Week 5. Categorical Independent Variables.

Session 9.  Tuesday, February 6th: Diagnostics
Berry. (Just get the main ideas for now; we’ll come back to these in more detail.)
Allison, pp. 119-135

Paper 2 due in class, at the beginning of class. Paper 3 handed out.
Data for Paper 3

Session 10. Thursday, February 8th: Dummy Variables.
Fox, pp. 135-145; Hardy, pp. 7-63; Allison, pp. 153-174.
 

Week 6.

Session 11. Tuesday, February 13th: Interaction Effects
Fox, pp. 145-154.

Session 12. Thursday, February 15th: Interaction Effects
Jaccard, Turrisi, Wan, pp. 7-49.
 

Week 7. Influential Points

Session 13. Tuesday, February 20th: Influential Points; Graphical Techniqes
Fox, pp. 267-294
Paper 3 due in class, at the beginning of class. Paper 4 handed out.
Data for Paper 4

Session 14. Thursday, February 22nd: Departures from Linearity and Normality
 

Week 8. Normality, Equal Variance, Linearity

Session 15. Tuesday, February 27th: More Diagnostics
Fox, pp. 59-82 and pp. 295-336

Session 16. Thursday, March 1st: Discussion : Statistics as a Method of Reasoning
McCloskey, “The Rhetoric of Significance Tests”, Comaroffs, “Ethnography and the Historical Imagination”,
and Collins, “Statistics Versus Words.”
 

Week 9.

Session 17. Tuesday, March 6th:  More Diagnostics
Paper 4 due in class, at the beginning of class. Paper 5 handed out.
Allison, pp. 49-96
Data for assignment Five at (under Announcements, "Data5"):
http://www.sscnet.ucla.edu/01W/soc210b-1/

Session 18. Thursday, March 8th: Departures from Linearity.
Fox, pp. 337-366
Allison, pp. 137-151
 

Week 10. Beyond the Linear Model

Session 19. Tuesday, March 13th: Collinearity
Fox, pp. 438-492.

Session 20. Thursday, March 15th: Other Models
Allison, pp. 175-187.
 

Paper 5 is due: March 23rd, by 4:00 in Hershey 2201.