Methods and Statistics in Political Science
Political Science 221
Hance Auditorium and Chambers 3187
Monday, Wednesday, Friday
10:30 – 11:20 p.m. (CRN 22808)
Spring 2007

Dr. Shelley Rigger Pryor 201B Office phone: 704-894-2505 Office Hours: M 12:30-2:30, T 8:30-10:00, W: 11:30-1:00, and by appointment Email: shrigger@davidson.edu Dr. Patrick Sellers Chambers 2039 Office Phone: 704-894-2078 Office Hours: M 4:30-5:30, W 11:30-1:00, F 12:30-3:00, and by appointment Email: pasellers@davidson.edu

Additional course materials

 Course Objectives

The world of politics offers a nearly infinite array of interesting and important problems.  Why did George Bush win the 2004 presidential election?  Is Europe's adoption of a common currency a merely superficial change or an important development fundamentally affecting the region's political and economic institutions?  Is Why religious fundamentalism thriving in Islamic countries?  For these and many other questions, potential answers may be difficult to sort out.  It is even harder to demonstrate conclusively that one of those answers is more "correct" than another.  This course will help you think more carefully and systematically about political questions, their potential answers, and the types of evidence needed to evaluate those answers.

To encourage such careful, systematic thinking, the course focuses on the analytical framework of statistics.  During the first part of the semester, we explore the logic of statistics without using numbers.  We examine how that logic can improve many types of non-quantitative analysis (i.e., research without "number crunching"), from historical analysis to single or comparative case studies.  The statistical principles can help make this type of research more logical and systematic.  However, the application of statistical principles to non-quantitative work is not universal and can be controversial; we will also discuss some of these controversies.  

During the second part of the semester, we examine the same statistical principles in their more common context: quantitative analysis with many observations.  With the growing availability of surveys and other large data sets, politicians and political scientists are increasingly turning to this type of analysis.  We begin with a discussion of averages and then move to basic concepts of probability and hypothesis testing.  We conclude with several weeks on correlation and regression, two of the most common types of statistical analysis.  These topics often create fear in the minds of political science majors, particularly those who chose the major in order to avoid all contact with numbers!  This course can alleviate such "stats anxiety."  Students are NOT required to have an extensive background in math or calculus.  Instead, they should understand basic math functions (addition, subtraction, multiplication, and division) and be willing to learn and apply additional math concepts.

Mastery of the course concepts can benefit students in many ways.  Here at Davidson, an understanding of statistical principles can help in other courses by making it easier to understand political science research presented in those courses.  You can impress friends and professors by posing important questions about that research: Why were the particular cases chosen for analysis?  Were these the best cases?  Does the evidence presented persuasively support the author's argument?  The concepts from this course can also make it easier for students to do their own research for seminar papers or honors theses.  Finally, the course can prove helpful after graduation.  In addition to developing their analytical and statistical abilities, students must improve their skills of written and verbal expression and learn a statistical computer program (Stata).  After graduation, these skills can make a student more attractive to potential employers.

Course Requirements

Each student’s grade for the course will be based on several components.  

• Graded problem sets.  Students will complete 5 problem sets.  Each individual problem set is worth 7% of the overall course grade.  The average of the problem set grades is worth 35% of the overall course grade.  Some assignments will require students to use the Stata statistical computer program.
• Midterm exam.  This exam is in class on October 5 and is worth 25% of the overall course grade.
• Final exam.  This exam is self-scheduled during the exam period and is worth 35% of the overall course grade.
• Weekly problems.  At the start of the semester, students will separate into small groups of 6-7 people each. Before several classes during the semester, students will receive (via email) a set of questions to answer, based on the subject material for that week. Each student is responsible for formulating answers before class on Friday. At the start of that class, we will break into the small groups and spend approximately 10 minutes discussing the questions and answers. Each group will then submit answers for grading (with the entire group receiving the same grade), and the class will then discuss the questions together. The average of the weekly problem grades is worth 5% of the overall course grade. The weekly problems help students apply and understand concepts from class. We strongly encourage students to come to class with completed answers, and to participate actively in their group discussions.  

Lateness policy: Work that is handed in after class on the day an assignment is due will be penalized 1/3 of a grade for each day it is late. That means that if you hand in an A+ paper at noon on the day the paper is due, you will receive an A. But no matter how late a paper is, it is always to your advantage to hand it in. Computer failure is not an acceptable excuse for lateness. Back up your work. If you are having printer trouble, email the paper as an attachment. Do not assume you have secured our permission for something unless you have spoken to usin person or received an e-mail or voice mail message from us.

Extensions: Please do not ask for extensions because you have “too much work;” everyone does, and it’s unfair to give extensions to those who ask, while those who don’t ask end up with less time to do a good job. Also, no extensions will be granted for extracurricular commitments. Look at your athletic, musical, union and theatrical schedules in advance, and plan your work accordingly.

Honor Code: Anything you hand in is pledged work. But as a reminder of the honor code's importance, we would like you to write out the honor code in full on the cover sheet of any work you hand in. ("On my honor I pledge that I have neither given nor received help on this work, nor am I aware of any violation on the part of others.") Please make sure you understand the honor code, especially the definition of plagiarism. If you have any questions, doubts or concerns about any aspect of the honor code, please come and talk to us. If you are unsure of how you should cite material used in an essay, please discuss it with us.  

Students must complete the two exams individually.  Students may work together to study for exams, as well as to complete problem sets and weekly problems. But, each student must submit his or her individual answers for the problem sets. We strongly encourage group effort; working together makes it easier to understand the problem and get the right answer!

Grading: The numerical grade for any assignment turned in may range from outstanding (in the 90-to-100 range) to failing (55).  Note that the failure to complete and turn in any assignment (problem set, weekly problem, or exam) will result in a numerical grade of 0 for that assignment.  When calculating final course grades, we will calculate the overall numerical averages and convert them to letter grades, where A=95, A-=91, B+=88, B=85, etc.

The required texts are available for purchase in the bookstore:

• R -- The Statistical Immagination, by Ferris Ritchey
• G -- Paradigms and Sand Castles, by Barbara Geddes
• P(EPA) -- The Essentials of Political Analysis, by Philip Pollock
• P(SCPA) -- A Stata Companion to Political Analysis, by Philip Pollock
• LB -- Applied Regression: An Introduction, by Michael Lewis-Beck

We will also read several individual articles and chapters. In the outline below, the name of each author is a hyperlink to the actual article or chapter. We may also add additional articles as the semester progresses; these will also be on electronic reserve. Finally, the course outline also mentions a number of optional readings, denoted as "KKV," which come from a book titled Designing Social Inquiry, by King, Keohane, and Verba. A copy of this book is on reserve in the library.