PS 672 - INTRODUCTION TO TECHNIQUES OF POLITICAL RESEARCH
(SPRING 2009)
Dr. Daniel S. Morey
1631 Patterson Office Tower
Class Meeting: T-TR 2:00 - 3:15 222 CP
daniel-morey@uky.edu
(859) 257-4234
Office Hours: T-Th 11-12, OBA
COURSE DESCRIPTION
This course provides students with the fundamental techniques to conduct political
research. Over the semester we will focus almost exclusively on the most fundamental
methodological technique – the linear regression model. We will learn the various aspects of the
‘classical’ regression model (including its basic assumptions) and its use in statistical inference.
We will then explore situations in which one or more basic assumptions are violated. Our
familiarity with the regression model will cover several topics, ranging from manual calculations
of relationships to computational calculations using large empirical datasets.
Course Texts
The following books are required reading during the semester. In addition, some class
discussions will incorporate articles from leading journals (available either on JSTOR or the
course website).
 William D. Berry. 1993. Understanding Regression Assumptions. Newbury Park: Sage
Publications.
 John Fox. 1991. Regression Diagnostics. Newbury Park: Sage Publications.
 Michael S. Lewis-Beck. 1995. Data Analysis: An Introduction. Thousand Oaks: Sage
Publications.
 Thomas H. Wonnacott and Ronald J. Wonnacott. 1990. Introductory Statistics 5th ed.
John Wiley & Sons.
Course Requirements and Assignments
Preparation and Participation (10%)
Since this is a graduate level seminar, participation is essential. You will never learn the material
if you do not engage in the course. Because uniformed participation does not help anyone learn,
part of participation is preparation. I expect each student to read all of the assigned material
before class. Individual participation scores will be based upon the quantity and quality of
answers and questions provided during the semester.
Note: coming to class late, or missing class without documentation of a very pressing
concern, is completely unacceptable in a graduate seminar. For each absence 5 percentage points
(100% - 5% = 95%) will be deducted from a student’s total course grade.
Homework Assignments (25%)
Periodically throughout the semester you will be assigned problem sets for analysis.
Calculations will be performed either manually (for smaller datasets) or using STATA (which
we will learn). You are allowed (and encouraged) to discuss the exercises with each other and
work in groups. However, the written results must be the product of your own labor, and
consequently are to be completed independently.
Midterm (30%) and Final Examination (35%)
Students are required to complete a midterm and final exam. Both exams are take home (open
book, open notes format). I distribute (via Blackboard) each exam approximately 1 week before
it is due. Hard copies are due at the start of the class on the assigned date. Both exams must be
completed independently.
Grading Policy
Final course grades will be assigned using the following scale:
A
B
C
E
100% - 90%
89.9% - 80%
79.9% - 70%
69.9% - 0%
In order to receive a passing grade in this course, ALL COURSE WORK MUST BE
COMPLETED. Any student who does not complete all the homework assignments, or take both
the midterm and the final exam, will receive an automatic grade of E.
Plagiarism and Cheating
Students are advised to retain all notes and drafts for all work until after they receive their
final grade. Students should also be aware that the instructor takes matters of plagiarism and
cheating very seriously and is prone to imposing the most severe penalty allowed by university
rules, which includes, but is not limited to, issuing an automatic grade of 0.0 for the entire
course.
Special Needs
If you have a documented disability that requires academic accommodations, please see
me as soon as possible during scheduled office hours. In order to receive accommodations in
this course, you must provide me with a Letter of Accommodation from the Disability
Resource Center (Room 2, Alumni Gym, 257-2754, jkarnes@email.uky.edu).
Classroom Expectations
I expect all students to behave professionally in this class. If you miss a class you are
still responsible for the information covered, and the instructor will not provide you with notes.
I expect all students who attend class to arrive on time and ready to start class. It is disrespectful
to the instructor and your classmates to show up late. During class please refrain from all
disruptive behavior, including (but not limited to) reading newspapers, sleeping, talking during
lecture, cell phone and pager use, and insulting classmates or the instructor.
Readings
The majority of readings come from the textbooks for this course. On occasion students
will be required to read a journal article or outside paper. These can be found either on the
course Blackboard page, on-line (jstor), or in the library. In the reading schedule I clearly
indicate where the student can locate the readings. Students are responsible for acquiring any
outside readings on their own.
Course Schedule
Below is a preliminary schedule of topics and readings for this course. The schedule is
subject to change based on the pace of the class. The instructor will clearly announce any
alterations to the course schedule (if any occur).
January 15th Introduction
Lewis-Beck, chapters 1-2.
January 20th – 22nd Review of Basic Statistical Theory
Lewis-Beck, chapters 3-5
January 27th – 29th Simple Regression
Lewis-Beck, chapter 6
Wonnacott and Wonnacott, chapters 11-12
February 3rd – 5th Simple Regression (continued)
No new readings
Note: February 5th lab day
Assignment: Homework #1 (distributed) February 5th
February 10th – 12th Multiple Regression
Lewis-Beck, chapter 7
Wonnacott and Wonnacott, chapter 13
Assignment: Homework #1 (due) February 12th
February 17th – 19th Multiple Regression (continued)
Note: No Class February 17th – ISA Conference
Fox, chapters 1-2
Lewis-Beck, Michael S. and Andrew Skalaban. 1990. “When to Use R-Squared.” The Political
Methodologist 3 (Fall): 9-11. [Blackboard]
King, Gary. 1990. “When Not to Use R-Squared.” The Political Methodologist 3 (Fall): 11-12.
[Blackboard]
Lewis-Beck, Michael S. and Andrew Skalaban. 1991. “Goodness of Fit and Model
Specification.” The Political Methodologist 4 (Spring): 19-21. [Blackboard]
Note: February 19th lab day
Assignment: Homework #2 (distributed) February 19th
February 24th – 26th Regression Assumptions
Lewis-Beck, chapter 9
Berry, chapters 1-6
Assignment: Homework #2 (due) February 26th
Exam: Midterm (distributed) February 26th
March 3rd – 5th Presenting Results
Nagler, Jonathan. 1995. “Coding Style and Good Computing Practices” (in
Verification/Replication). PS: Political Science and Politics 28 (3): 488-492.
King, Gary. 1986. “How Not To Lie With Statistics: Avoiding Common Mistakes in
Quantitative Political Science.” American Journal of Political Science 30: 666-687.
Gelman, Andrew; Cristian Pasarica; Rahul Dodhia. 2002. “Let's Practice What We
Preach: Turning Tables into Graphs.” The American Statistician 56 (2): 121-130.
Kastellec, Jonathan P. and Eduardo L. Leoni. 2007. “Using Graphs Instead of Tables in
Political Science.” Perspectives on Politics 5 (4): 755-771. [Cambridge]
Note: March 5th lab day
Exam: Midterm (due) March 5th
March 10th – 12th Specification and Diagnostics
Fox, chapters 4-5, 8-10
March 17th - 19th NO Class (Spring Break)
March 24th – 26th Collinearity, Dummy Variable Regression Models, and Non-Linearity
Fox, chapters 3, 7
March 31st – April 2nd Heteroscedasticity
Fox, chapter 6
Note: April 2nd lab day
Assignment: Homework #3 (distributed) April 2nd
April 7th – 9th Autocorrelation
Ostrom, Charles W., Jr., and Francis W. Hoole. 1978. “Alliances and Wars Revisited: A
Research Note.” International Studies Quarterly 22 (June): 215-236.
Assignment: Homework #3 (due) April 9th
April 14th – 16th Endogeneity
Note: April 16th lab day
Assignment: Homework #4 (distributed) April 16th
April 21st - 23rd The Regression Model Using Matrix Algebra
Assignment: Homework #4 (due) April 23rd
April 28th – 30th Non-Linear and Qualitative Response Regression Models
Lewis-Beck, Michael S. and Daniel S. Morey. 2007. “The French “Petit Oui”: The Maastricht
Treaty and the French Voting Agenda.” Journal of Interdisciplinary History 38 (1): 6587. [EBSCOhost]
Note: April 30th lab day
Exam: Final (distributed) April 30th
May 7th Final Exam Due (1 PM)