Introduction to Data Analysis for Sociology Graduate Students
rev: 9/14/2012
Syllabus
Fall Quarter, 2012
Tuesdays and Thursdays
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)
Kate Weisshaar (weisshaar@stanford.edu)
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
Books required (available at Stanford Bookstore):
* Tufte, Edward. 2001. The Visual Display of Quantitative Information. Graphics Press. ISBN-10: 0961392142. $30
* Statistics with Stata ver 12, by Lawrence C. Hamilton. 2013, Brooks/Cole. ISBN-10: 0840064632. $75
Recommended Books:
* Mathematical
Statistics and Data Analysis, by John Rice, Duxbury Press, 3rd edition
2006, ISBN-10:
0534399428. $175
* Freedman, David, Robert Pisani,
and Roger Purves. 2007. Statistics. Fourth Edition. W.W. Norton. $125. ISBN-10: 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:
* Hamilton is a good practical book about how to get things done in Stata. Even experienced Stata hands will learn something from this book.
* 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 12. You may purchase either a 1 year license for $98,or a perpetual license for $179. 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/gp-direct.html
Note that the Graduate Student Computer Lab currently runs Stata version 10, Professor Rosenfeld will be using Stata version 11, and students who buy Stata will be getting Stata version 12. These versions work pretty much the same way.
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:
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Project 2 (Data analysis and interpretation) homework |
4 homeworks, 10% each |
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Regular section participation |
5% |
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In-class presentation (data analysis of dataset of your own choosing) outline |
5% |
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In-class presentation (data analysis of dataset of your own choosing) actual presentation to class |
20% |
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Final Exam |
30% |
Project and Reading Assignment Timeline
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Week |
CLASS |
Class lecture Goals |
READING (Readings in bold are required and will be discussed specifically in that class. Other readings are supplementary) |
ASSIGNMENT |
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1 |
Sept 25 |
Introduction to Stata and Data Analysis Section |
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Hand out |
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Sept 27 |
Basics of descriptive data analysis using STATA |
Read Hamilton, chapters 1 and 2 (Introduction, and Data Management) and Hamilton’s Chapter 5 (Summary Statistics and Tables). Read Rosenfeld’s online Stata guide
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section |
Work on HW 1 and on using STATA |
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2 |
Oct 2 |
Observational Studies and their limitations |
Freedman Ch 2, 4 |
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Oct 4 |
Error and bias |
Freedman Ch 6 |
HW #1 due Hand out HW#2 |
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section |
Stata, and HW 2 |
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3 |
Oct 9 |
Probability sampling, Sample size and power, and standard errors |
Freedman Ch 20; read also Hamilton, Ch 7, Linear Regression Analysis; Rice, ch. 6 |
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Oct 11 |
More on sample size and power. |
Freedman Ch 21 Rice, p. 398-411 |
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section |
Work on STATA, discuss the issues in HWs 2 and 3 |
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4 |
Oct 16 |
Introduction to regression with STATA |
Freedman Chs 9, 10 |
HW #2 Due Hand out HW#3 |
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Oct 18 |
More on regression with STATA, interpreting coefficients |
Freedman, Ch 11; Rice ch. 14 |
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section |
Work on STATA, discuss the issues in |
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5 |
Oct 23 |
Problems with and difficulties in using regression, Graphing. |
Freedman Ch 12 |
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Oct 25 |
More limitations of regression analysis |
Tufte, P. 1-87 |
HW #3 due Hand out HW #4 |
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section |
Work on STATA |
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6 |
Oct 30 |
Proper and improper presentation of data |
Tufte, P. 90-190, Hamilton on regression diagnostics, 192-209 |
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Nov 1 |
Regression analysis: residuals and outliers |
Readings by Jasso and Kahn and Udry, posted on class website |
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section |
work on HW 4 |
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7 |
Nov 6 |
Other topics, including logistic regression |
Hamilton Ch 9, logistic regression; Rice p. 253-268 |
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Nov 8 |
More on logistic regression |
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HW #4 due |
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8 |
Nov 13 |
Some additional, and advanced topics |
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Nov 15 |
Some additional, and advanced topics |
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Presentation Proposals Due |
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Week of Nov 19-23 |
Thanksgiving break |
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9 |
Nov 27 |
Some additional, and advanced topics/ Student Presentations |
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Nov 29 |
Student Presentations |
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10 |
Dec 4 |
Student Presentations, and some Final Exam Review |
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Dec 6 |
Student Presentations, and some Final Exam Review |
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Final Exam |
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Final Exam at the regularly schedule time and place |
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