POLS 340: Undergraduate Research Methods
Tuesday and Thursday, 11:00-12:15
Dusable 170 and McMurray 208
Fall 2005
Dr. Matt Streb
Office: Zulauf 412
E-MAIL: mstreb@niu.edu
Office Hours: Tuesday and Thursday, 3:30-4:30; Wednesday, 9-12
Phone: 753-7046
“Statistical thinking will one day be as necessary a qualification
for efficient citizenship as the ability to read and write.”
--H.G. Wells
Course Description: The world of politics offers a nearly infinite array of interesting questions. Why did George W. 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? Why has religious fundamentalism thrived in Islamic countries? Do Supreme Court justices generally follow precedent when making their rulings or their own personal beliefs? Does a cultural divide exist in the United States? For these and literally thousands of other questions, potential answers may be difficult to sort out, and 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.
The first half of this course introduces students to social science research by discussing how one develops a research question and hypotheses. The second part of the course provides students with the tools necessary to test hypotheses systematically and quantitatively. This does mean that you will learn some basic statistics. Many students get ill when they find out that they are required to take a quantitative methods course to graduate (I was one of them!), but learning data analysis can be extremely beneficial to you in the future and even fun.
You probably won’t believe this now, but a course on quantitative methods can benefit every student in different ways. While still in school, the course will help you in other courses by making it easier to understand political science research and leading you to ask important questions about that research. In addition, a basic knowledge of statistics also makes students more attractive to potential employers in a wide-range of fields. This course will also help those of you who are headed to a graduate program in social science by providing you with a background in the tools necessary to excel in that program. We don’t require the course to punish you; we require it because it is important and useful. Who knows? You might shock yourself by deciding you want to take another statistics class! I certainly never imagined when I walked in to my first methods class that I would end up teaching it for a living!
Grading:
Your grade will be based on the following components:
The reading load for this course if very light. On the other hand, you will be expected to complete six take home assignments during the semester, each worth 5% of your final grade. These assignments will require a fair amount of work, so procrastination is not encouraged. Read the assignment when you receive it and be sure to leave yourself plenty of time to complete it. An assignment is considered to be late if it is not turned in at the beginning of class on the day it is due. Late assignments will be penalized one letter grade per day (including Saturdays and Sundays) and will not be accepted after five days.
Several of these assignments will require you to use the
statistical program SPSS. We will work
through several SPSS exercises in class together and then you will be required
to do some assignments outside of class.
We will meet in Dusable 170 when we use SPSS. Because Dusable 170 is not very conducive to lecturing, however,
we will meet every Tuesday (unless otherwise noted) in McMurray 208.
The two in-class examinations will be held on Tuesday, September 27th and Tuesday, December 6th (10 AM).
Finally, participation will constitute 10% of your final
grade. I have no formal attendance
policy, but I will take attendance in class and your participation grade will
depend on how frequently you attend and how much you participate
(constructively) in class discussion. Do not take your participation grade for
granted!
Grading Scale:
93%-100% A 90%-92.9% A- 87.5%-89.9% B+
83%-87.4% B 80%-82.9% B- 77.5%-79.9% C+
73%-77.4% C 70%-72.9% C- 67.5%-69.9% D+
63%-67.4% D 60%-62.9% D- Less than 60% F
Required Course Materials:
Two books are required for this course:
Johnson, Janet Buttolph, and H.T.
Reynolds. 2005. Political
Science Research
Methods, 5th ed. Washington, D.C.: CQ Press.
Pollock III, Philip H. 2005. An SPSS Companion to Political Analysis, 2nd ed.
Washington, D.C.: CQ Press.
These books are available at the NIU bookstore.
You may have also noticed that a fee was required to take this course. That fee allows you access to the SOCQRL Computer Lab in DuSable 222. You will be able to do your assignments in the SOCQRL Lab and have trained tutors available to help you. The lab is open Monday-Thursday from 12PM-10PM, Friday from 8AM-5PM, and Sunday from 6PM-10PM. You can visit the SOCQRL webpage (ww.socqrl.niu.edu) for more information. If you have questions, please do not hesitate to ask.
How Can I Do Well in
this Course?:
This class will be different from previous political science courses you have had. Because it is different, students sometimes struggle with the material. Therefore, it is imperative that you attend class and keep up with the readings. If you get behind, you will find that it is extremely difficult to catch up. Also, students are strongly encouraged to ask questions during lectures or visit me during my office hours. Don’t be shy. If you don’t understand something, I guarantee someone else in the class doesn’t understand it as well. Finally, cheating and plagiarism will not only keep you from learning the material, they will get you an F in the class and possible suspension or expulsion from school. See the Student Handbook for more information on cheating and plagiarism.
Course Outline:
NOTE: Readings should be finished by class time on
the day they are assigned. For example,
students should have read Johnson and Reynolds, chps 1-2 by August 25th. JR is the
abbreviation for the Johnson/Reynolds book.
P is the abbreviation for the Pollock book.
*On the dates that are italicized, we will meet in McMurray 208.
T August 23rd Introduction to the Course
R August 25th Studying Politics Scientifically (JR, chps 1-2)
T August 30th Creating
a Research Question and Developing Your Hypotheses
(JR, chps 4-5)
R September 1st NO CLASS. APSA Conference
T September 6th Measuring Variables (JR, chp 6)
R September 8th Measuring Variables, cont.
T September 13th Implementing the Research Design (JR, chp
3)
R September 15th Implementing the Research Design, cont.
ASSIGNMENT
#1 DUE
T September 20th Making Empirical Observations (JR, chp 7)
R September 22nd Midterm Review
T September 27th MIDTERM
R September 29th Introduction to SPSS/Making Comparisons
(P, “Getting Started,”
chps 1, 3)
T October 4th Collecting Data: Document Analysis
(JR, chp 8)
ASSIGNMENT #2 DUE
R October 6th SPSS: Transforming Variables in SPSS (P, chp 4)
T October 11th Sampling (JR, chp 9)
R October 13th SPSS: Making Controlled Comparisons (P, chp 5)
T October 18th Survey Research (JR, chp 10)
R October 20th Univariate Statistics/SPSS:
Descriptive Statistics (JR, chp 11; P,
chp 2)
T October 25th Bivariate Statistics (JR, pp. 339-371)
ASSIGNMENT #3 DUE
R October 27th SPSS: Making Inferences about Sample Means (P, chp 6)
T November 1st SPSS: Chi-Square and Measures of Association (P, chp 7)
R November 3rd Regression and Correlation (JR, pp.
372-402)
ASSIGNMENT
#4 DUE
T November 8th Regression and Correlation, cont.
R November 10th SPSS:
Correlation and Linear Regression (P, chp 8)
T November 15th Multiple Regression (JR, pp. 403-428)
ASSIGNMENT
#5 DUE
R November 17th SPSS: Dummy Variables and Interaction Effects (P,
chp 9)
T November 22nd Logistic Regression (JR, pp. 429-451)
ASSIGNMENT
#6 DUE
R November 24th NO CLASS.
HAPPY THANKSGIVING!
T November 29th SPSS: Logistic Regression (P, 10)
R December 1st Review for Final Exam
T December 6th FINAL EXAM (10AM)