The
world of politics offers a nearly infinite array of interesting
problems. Why did George Bush win the 2000 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? Why has religious fundamentalism thrived 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 other 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 the Stata statistical computer program.
After graduation, these skills can make a student more attractive to potential
employers.
Thus, while you may not have come to college just hoping to take a Political Science course in methods and statistics, we trust that you will find it a useful part of your liberal arts education. All citizens should have at least a basic understanding of how to interpret statistical concepts. Complex political questions can often benefit from the type of analysis that we will do in this course. This course is required for the major, and we encourage students to take it as soon as possible after declaring.
Joel Best – Damned Lies and Statistics, U. California Press, 2001.
Marcus Ethridge (ed.) – The Political Research Experience (3rd ed.), M. E. Sharpe, 2002.
Ferris Ritchey – The Statistical Imagination, McGraw Hill, 2000.
Some additional reading is available on electronic reserve.
Coming to class on a regular basis matters in most
Davidson classes, but more than usual in this one.
Do the reading, be in class, work on the problems, and you will be in
great shape for the exams. Since
the problems often depend on the material discussed in the previous class,
taking good notes will help you a lot. Note
that Davidson academic regulations call for failing grades to be given to any
student who misses more than 25% of the scheduled classes.
Although much can be learned by reading about methodology, the only way to develop real skill is to work through problems. On average, you will have two daily problems a week. They will be due on Mondays and Fridays. These are short assignments, which will be based on reading and class discussion. You may feel free to talk with other class members and to work on these problems together. My general rule is that you should spend at least fifteen minutes trying on your own to understand what is going on. Consult with others for another fifteen minutes. If you are still lost at that point, email me or come by my office.
There will be 20 daily problems altogether. I will record grades for only the highest 18.
In addition to the Daily Problems, there will be five problem sets due during the course of the semester. These are longer assignments that will take several days to complete. All work should be typed when possible, though equations may need to be written by hand.
Honor Code
The Honor Code binds all work in the course. In accordance with the Honor Code, all paper assignments must provide appropriate citations for any sources or information included in the paper; failure to provide these citations is a violation of the Honor Code. If you have questions about the appropriate format for citations, make sure that you ask us before turning in the paper. You can also visit the Campus Writing Center for additional assistance, especially with citations. If you have any questions about how to apply the Honor Code to work in this course, please do not hesitate to ask.
Studying in groups can be of immense help in a statistics course. I will provide some guidance in forming study groups. Discussing the homework in groups is not a violation of the Honor Code. Once you begin to write the answers, however, the work should be your own.
One skill that should always be a part of liberal arts is the ability to deliver an interesting oral presentation. As part of this course, you will be required to do a five -minute presentation illustrating a topic in the course. A hand-out prepared in consultation with Prof. Bonnie McAlister of our speech department will guide you in issues to consider. I will assign specific dates for your topic during the first week of class. You will do a very short practice presentation the second day of class and then get some quick feed-back on how to prepare for your major presentation.
You will also critique the presentation of several other students using the guidelines mentioned above. These comments will be emailed to me. I will edit them and then forward them to the student who made the presentation. You will be graded on the depth and perception of your critique.
Click here to view class presentations
In addition to the items listed above, there will be an in class mid-term and a self-scheduled final. The weights of these various factors are: 5 problem sets—4% each; 18 daily problems –1% each; 1 oral presentation – 5%; 7 evaluations of presentation – 1% each; mid-term – 20%; final – 30%.
Since we will often be discussing the daily problems and problem sets in class the session after they are due, you may not get any credit if the problem is handed in after that time. Any late work will be penalized at the rate of 5 points per day. The beginning of class is the time all work is due. If you are sick, contact me at once. Emailing me work is acceptable only with specific prior permission. I expect hard copy for all assignments.
My tentative office hours will be: MWF 9:30-10:20; TTh 2-4.
Emailing me is better than calling.
Tentative Schedule
January 13 – Introduction; list preferred presentation dates
15 – Best: 1-29; brief oral presentation
* 17 – Best: 30-44; Ethridge 3-19; Hill (electronic reserve)
20—MLK day: no class
22—Ethridge 20-41; Ritchey 17-19
*24—Ethridge 41-57
*27—Ethridge 58- 79
29—Ethridge 79—95; Best 45-52
31 – Problem set #1 due
*February 3 – Ethridge 96-120
5—Ethridge 120-143, 150-152
* 7—Ethridge 153-160, 186-204
*10—Ethridge 205-222
12 – Best 59-95
14 – Problem set # 2 due
* 17 – Best 96-127
February 19 – Best 128- 171
* 21 – Putnam (electronic reserve)
*24 – Ritchey 1-30
26 – Summary of Part I
28 – Mid-term
March 3-7 – Spring Break
10— Ritchey 32-70; Best 52-58
12 – Ritchey 96-121; Ethridge 285-305
*14 -- Ritchey 122-153
*17—Ritchey 154-162
19 – Ritchey 163-188
*21 – Ritchey 189 – 200; Ethridge 244-264
*24 – Ritchey 200-214
26 – Ritchey 221-241
28 – Problem Set # 3 due
*31 – Ritchey 241-245
April 2 – Ritchey 249-287
*4 – Ritchey 288-317
* 7 – Ritchey 318-333
9 – Ritchey 334-351
11-- Problem Set # 4 due
*14 – Ritchey 351-375
16 – Ritchey 421-436
*April 18 – Ritchey 460- 468
21 – Easter Break
23 – Ritchey 468-484; Ethridge 120-143
* 25—Ethridge 321- 336
*28 – Ethridge 336-364
30 – Ritchey 524-554; Ethridge 306-320
May 2—Problem Set # 5 due
5 – Ethridge 365 - 377
Days marked with an * indicate when a daily problem will be due.