Introduction to Data Analysis for Sociology Graduate Students
rev: 9/23/2013
Syllabus
Fall Quarter, 2013
Tuesdays and Thursdays
2:153:30
Education building, room 130
Lab/Section once a week time and place TBA
Michael J. Rosenfeld
Associate Professor
Department of Sociology
Building 120 room 124
The class website is my personal Stanford website
Office Hours by appointment
TAs:
Anna Lunn alunn@stanford.edu (leads homework section)
Jacob Reidhead reidhead@stanford.edu (leads research project section)
Introduction:
In this class you will teach yourself basic statistics including regression, how do statistical analysis, and how to find flaws and problems with statistical analyses.
In the process of learning about data analysis you will also learn about demography and stratification in the U.S., because the dataset is the Current Population Survey of March, 2000, which is a nationally representative survey of more than 60,000 households, with lots of information about race, gender, income, occupation, place of residence, and so on. You'll also learn how to use one of the most powerful and flexible tools for data analysis, the statistical software STATA.
Readings and Grading Policy
Books required (available at Stanford Bookstore):
* Tufte, Edward. 2001. The Visual Display of Quantitative Information. Graphics Press. ISBN10: 0961392142. $30
* Treiman, Donald. 2009. Quantitative Analysis: Doing Social Research to Test Ideas. JosseyBass. ISBN10: 0470380039. $59
Recommended Books:
* Mathematical Statistics and Data Analysis, by John Rice, Duxbury Press, 3rd edition 2006, ISBN10: 0534399428. $175
* Freedman, David, Robert Pisani, and Roger Purves. 2007. Statistics. Fourth Edition. W.W. Norton. $125. ISBN10: 0393929728
The most important readings for the class are the Excel files, Stata logs, and PDF documentation posted on my website. Aside from the Tufte book, which we will be talking about specifically in class, the other books are all supplementary. That is, you don’t need the books. This is briefly why you should own the books anyway:
* Treiman is an excellent book about social statistics (using Stata), which covers some practical aspects of data analysis that we won’t get to in this class.
* Freedman is a classic introductory text about statistics, with no math, but with very good plain English explanations. If you don’t have a math background, Freedman’s explanations may be helpful to you. If you do have a math background, the Freedman may help you explain statistics to other people. And if you end up teaching undergraduate statistics in the future, you may be teaching from Freedman.
* Rice is a classic introduction to statistics for readers who have at least a modest familiarity with calculus. Rice offers outlines of proofs and lots of great problems you can work through on your own. Rice is a great reference book that you should have on your shelf if you plan on doing any data analysis.
Software Required
* You will need Stata in order to do the homework for Soc 381. You have several options:
1) The least easy and the least palatable is to use Stata over Unix. This is free but very cumbersome.
2) Stata is installed in the graduate student computer cluster, running on Windows PCs. This is a good solution, except that you won’t have access to Stata in class or when you are home.
3) The option that offers the most convenience, but also costs the most, is for you to buy a licence for Intercooled (IC) Stata, Version 13. You may purchase either a 1 year license for $98,or a perpetual license for $189. I recommend the perpetual license so that you can use this software in the future. The software comes with a small introduction to Stata book. Don’t bother buying Stata’s massive printed reference book collection for this class. I will teach you the Stata commands that you need to know, and the Stata online help is very good.
http://www.stata.com/order/new/edu/gradplans/campusgradplan/
Note that the Graduate Student Computer Lab currently runs an earlier version of Stata. Different versions of Stata work pretty much the same way.
Students with Disabilities:
Students with Documented Disabilities: Students who may need an academic accommodation based on the impact of a disability must initiate the request with the Office of Accessible Education (OAE). Professional staff will evaluate the request with required documentation, recommend reasonable accommodations, and prepare an Accommodation Letter for faculty dated in the current quarter in which the request is made. Students should contact the OAE as soon as possible since timely notice is needed to coordinate accommodations. The OAE is located at 563 Salvatierra Walk (phone: 7231066, URL: http://studentaffairs.stanford.edu/oae).
Units:
This Course justifies an additional unit of credit, beyond what would be expected based on the typical assignment of class time and outside work. An additional unit represents, on average, 30 additional hours of work expected of a student during the quarter, devoted to homework and to the preparation of the student’s research presentation.
Computer Use Policy:
* Computer use by students during class is strictly limited to following along with the data analysis examples being presented by the professor.
Grading:
Project 2 (Data analysis and interpretation) homework 
4 homeworks, 10% each 
Regular section participation 
5% 
Inclass presentation (data analysis of dataset of your own choosing) outline 
5% 
Inclass presentation (data analysis of dataset of your own choosing) actual presentation to class 
20% 
Final Exam 
30% 
Project and Reading Assignment Timeline
Week 
CLASS 
Class lecture Goals 
READING (Readings in bold are required and will be discussed specifically in that class. Other readings are supplementary) 
ASSIGNMENT 
1 
Sept 24 
Introduction to Stata and Data Analysis Section 

Hand out CPS HW #1 

Sept 26 
Basics of descriptive data analysis using STATA 
Read Treiman’s chapters 14. Read Rosenfeld’s online Stata guide



section 
Work on HW 1 and on using STATA 







2 
Oct 1 
Observational Studies and their limitations 
Freedman Ch 2, 4 


Oct 3 
Error and bias 
Freedman Ch 6 
HW #1 due Hand out HW#2 

section 
Stata, and HW 2 







3 
Oct 8 
Probability sampling, Sample size and power, and standard errors 
Freedman Ch 20; read also Treiman Ch 9; Rice, ch. 6 


Oct 10 
More on sample size and power. 
Freedman Ch 21 Rice, p. 398411 


section 
Work on STATA, discuss the issues in HWs 2 and 3 







4 
Oct 15 
Introduction to regression with STATA 
Freedman Chs 9, 10 Treiman, Ch 56 
HW #2 Due Hand out HW#3 

Oct 17 
More on regression with STATA, interpreting coefficients 
Freedman, Ch 11; Rice ch. 14 


section 
Work on STATA, discuss the issues in CPS HW #3 







5 
Oct 22 
Problems with and difficulties in using regression, Graphing. 
Freedman Ch 12 


Oct 24 
More limitations of regression analysis 
Tufte, P. 187 Tufte, P. 90190, Treiman chapter 10 
HW #3 due Hand out HW #4 

section 
Work on STATA 







6 
Oct 29 
Proper and improper presentation of data; Regression analysis: residuals and outliers 
Readings by Jasso and Kahn and Udry, posted on class website 


Oct 31 
Logistic regression 
Treiman chapter 13 Rice p. 253268 


section 
work on HW 4 







7 
Nov 5 
Other topics, including logistic regression 


Nov 7 
Other topics 

HW #4 due 






Sunday, November 10 


Presentation Proposals Due 
8 
Nov 12 
Some additional, and advanced topics 



Nov 14 
Some additional, and advanced topics 







9 
Nov 19 
Some additional, and advanced topics/ Student Presentations 



Nov 21 
Student Presentations 








Nov 2529 
Thanksgiving break 







10 
Dec 3 
Student Presentations, and some Final Exam Review 



Dec 5 
Student Presentations, and some Final Exam Review 












Final Exam 

in class Final Exam at the regularly schedule time and place 

