Political Science 340: Introduction to Political Analysis
Spring 2011, Professor Mikel Wyckoff
Office: Zulauf 426 (enter through Zu 415)
Hours: M&W and by appointment
Contact: email@example.com 753-7056
TA: Mr. Mark Jerkatis
Office: DuSable 476 (hours tba)
Scholars in the Political Science discipline address a wide variety of research problems and they do so using a number of different research methods and strategies. This methodological pluralism is good, because no single method is appropriate for all problems that we encounter. If we choose to define the term “science” in a rigorous way, however, this implies the need to subject our explanations of things (our theories about how things work) to empirical evidence that has been systematically gathered and analyzed. Scientists, after all, are those people who are in the business not just of arguing about the nature of reality, but of conducting empirical tests of hypotheses, and by doing so as carefully and thoughtfully as we can. The purpose of POLS 340, then, is to introduce students to the scientific side of our discipline. We begin with a brief examination of science as a philosophy of knowledge. With that understanding in hand we then consider a wide range of strategies and tools that can help us conduct meaningful research.
Students who complete this course will be better prepared to take several of our upper level courses that stress the importance of data collection and analysis – courses devoted to political parties, voting behavior, public opinion, and political participation, to name a few. POLS 340 will also help prepare you to take more advanced courses in statistical methods in the Math Department and elsewhere, and it should provide you with basic scientific literacy needed to be an effective consumer of news in the 21st Century.
Michael K. LeRoy, Research Methods in Political Science (7th ed.), Thompson-Wadsworth, 2009 (new books only to ensure availability of required software).
W. Phillips Shively, The Craft of Political Research (7th ed.), Pearson-Prentice Hall, 2009.
Additional required readings, from time to time, in the form of articles that can be located online and/or handouts distributed in class.
Cell Phones and Classroom Decorum. Please silence and refrain from using your cell phone and other electronic devices during class. In addition, please be civil, use common sense, and respect the needs of your fellow students.
Attendance/Participation (10%). Ten percent of your class grade is based on attendance and participation, so I expect you to arrive on time and to come prepared to discuss assigned readings and computer exercises. Attendance will be taken during the first ten minutes of class each day and late arrivals will be treated as unexcused absences. Everyone is allowed two unexcused absences. After that, your grade for participation will be reduced by one letter for each unexcused absence. Excused absences are defined below under the topic of makeup exams.
Exams (25% each). A midterm and a final exam will be given. The midterm will emphasize the research design issues found in Part I of the course outline. The final will emphasize the statistical material found in the second half of the syllabus.
Makeup Exams will be provided cheerfully when needed, but only for reasons of significant illness, family tragedy, participation in NIU intercollegiate events, or other extraordinary circumstances. Furthermore, documentary evidence normally must be provided by the student. Incompletes will be given only in exceptional circumstances and they must be negotiated prior to the last day of class (August 5).
Computer Exercises (20%). A set of 10-12 statistical exercises, to be conducted using a data analysis program called MicroCase, will be assigned over the course of the semester. No one should feel intimidated by these assignments. Indeed, most of you will find these exercises easier than the exams. No prior knowledge of statistics is required, the software is very user friendly, and a lab assistant will be available to help when help is needed (for more details about the lab, see below under the topic of “course fees”). Due dates for the assignments are noted in Section IV below. Normally, if an exercise is not turned in during class on its due date, the highest grade it can achieve is 50% of the maximum possible score, and any exercise submitted over 24 hours late will receive a score of zero. If an excused absence occurs, the due date normally will be moved to the next scheduled class period.
Original Data Analysis (20%). Each student will select, from among the seven data files included with our textbook (see p. 6, for example), a data set of interest to him/her, identify a research question that can be addressed using that data, locate at least three articles in the professional political science literature (see, for example, JSTOR.org) that shed light on the research question, test a causal hypothesis using variables contained in the data set, and write up the results (approximately 8-10 pages). Your analysis should examine, first, the bivariate relationship suggested by your main hypothesis. Subsequently you will introduce at least two control variables to see what happens to the original relationship when additional variables are held constant. This is a multi-stage project involving the following elements:
· After exploring available data sets and after consulting the political science literature you will identify a research problem (and a related, dependent variable) of interest to you, and you will locate and discuss at least three directly relevant research articles that have investigated this problem in the past. (3 page paper due by Feb. 28, worth 5 points).
· A preliminary paper outlining: (1) one or more specific hypotheses to be tested; (2) the data you expect to use to operationalize the variables in your hypotheses; (3) your plan for analyzing the data. (3 page paper, due by April 18, worth 5 points).
· Final draft of your completed analysis (worth 90 points). Your final report should be approximately 8-10 pages (typed and double-spaced). All papers are due by Monday, May 2. Late papers will be penalized at the rate of one-third of a letter grade per day.
Grading System. In summary, final grades will be computed as follows:
Exam I 25%
Exam II 25
Computer Exercises 20
Original Data Analysis 20
When I compute your course grade I will use the following formula in my spreadsheet to generate a weighted average:
Wtd. Avg. = .25(Exam I) + .25(Exam II) + .20(avg. exercise score) + .20(orig. analysis) + .10(Attend.)
Grades will be assigned on the basis of performance, not student need. If you need a certain grade in this course to graduate on time, or to maintain your academic standing with the university, or for whatever reason, then I will be glad to work with you to help you do your best on the exams and other course requirements. In the end, however, your course grade will be based on the quality of your performance on required exams, papers, computer exercises and class participation.
Course Fees. Your course fees provide access to the Department of Sociology’s Quantitative Research Lab (SOCQRL), located in DuSable 222. The SOCQRL has the equipment and software you need to do the computer exercises in this course and it is staffed by graduate students who are familiar with the research process generally and with the MicroCase analysis system used in POLS 340. To check out their hours go to http://www.socqrl.niu.edu/
Academic Integrity and Plagiarism: Plagiarism and other forms of academic dishonesty are serious offenses that can and do result in serious penalties. Regarding plagiarism, the NIU Undergraduate Catalog states: "Students are guilty of plagiarism, intentional or not, if they copy material from books, magazines, or other sources (including the Internet) without identifying and acknowledging them. Students guilty of, or assisting others in, either cheating or plagiarism on an assignment, quiz, or examination may receive a grade of F for the course involved and may be suspended or dismissed from the university." The above statement encompasses a paper written in whole or in part by another; a paper copied word-for-word or with only minor changes from another source; a paper copied in part from one or more sources without proper identification and acknowledgment of the sources; a paper that is merely a paraphrase of one or more sources, using ideas and/or logic without credit even though the actual words may be changed; and a paper that quotes, summarizes or paraphrases, or cuts and pastes words, phrases, or images from an Internet source without identification and the address of the web site.
If you need more information about plagiarism, please consult the “Statement on Plagiarism,” prepared by NIU’s English Department, that I have posted on Blackboard. It may also be informative to do the online tutorial available on NIU’s Academic Integrity web page at http://www.ai.niu.edu/ai/. It is your responsibility to educate yourself with regard to these issues. Ignorance is not an acceptable excuse for breaking the rules.
SafeAssign. All students must submit an electronic copy of your final paper (in addition to a hard copy) on Blackboard where each paper will be processed by Safe-Assign, a computer program that checks documents for instances of plagiarism. In short, if you “borrow” somebody else’s text and try to present it as your own there is an excellent chance that you will get caught. Please do your own work and write in your own voice, not somebody else’s.
Students with Disabilities. NIU abides by the Rehabilitation Act of 1973 which mandates reasonable accommodations for qualified students with disabilities. If you have a disability and may require some type of instructional or examination accommodation, please let me know. If you have not already done so, you will need to register with the Center for Access-Ability Resources (CAAR). The CAAR office is located on the 4th floor of the University Health Services building (753-1303).
A. Introduction to the course and to the MicroCase software (January 19 & 24)
Read: Corbett and LeRoy, “Getting Started” and Ch. 1, “Overview of Research Methods.”
Krauthammer, "Let's Have No More Monkey Trials," locate online at:
Dawkins and Coin, “In Science, Fact, Not Faith, Measures Ideas’ Validity,” available in
Documents section of Blackboard.
Shively, Ch. 1, especially pp. 1-8.
Worksheet 1 is due Wednesday, January 26.
Suggested Reading: Robert Pirsig, Zen and the Art of Motorcycle Maintenance
B. Measurement: Abstract Concepts vs. Empirical Indicators (January 26, 31 & February 2)
Read: Corbett and LeRoy, Ch. 2.
Diamond, "Soft Sciences Are Often Harder Than Hard Sciences,” at:
Sears, et al., “Is It Really Racism?” Public Opinion Quarterly 61 (1997). Find at
http://www.jstor.org/. Read pp. 16-28 only. For now, focus primarily on the twin problems of
defining the abstract concept of “racism” and how best to go about measuring racist
attitudes and beliefs.
Shively, Ch. 3, pp. 32-37; Ch. 4, especially pp. 45-52.
Worksheet 2 is due Wednesday, February 2.
C. Varieties of Data (Levels of Measurement) and Data Collection Methods (February 7, 9, 14)
Read: Corbett and LeRoy, Ch. 3.
Shively, Ch. 5, pp. 57-66; Ch. 6, pp. 74-84.
Nelson, et al., “Media Framing of a Civil Liberties Conflict …” American Political
Science Review 91 (1997). Find at http://www.jstor.org/. Read pp. 567-572 only. This is
an experimental study. What makes it so? What are its strengths and weaknesses?
Also, think consciously about the theory that is being tested in this study.
Worksheet 3 is due Monday, February 14.
D. Variables, Variation and Explanation (February 16 & 21)
Read: Corbett and LeRoy, Ch. 4.
Shively, Ch. 6, pp. 94-95.
Easton and Dennis, “The Child’s Acquisition of Regime Norms,” American Political
Science Review 61 (1967): 25-38. Find at http://www.jstor.org/. Skim some of this while reading
for main ideas; think hard about the relationships observed in Tables 2-5.
Worksheet 4 is due Wednesday, February 23.
E. Theories and Hypotheses (February 23 & 28)
Read: Corbett and LeRoy, Ch. 5.
Shively, Ch. 2, pp. 13-17, 22-31.
Review articles by Sears, et al. (1997), Nelson et al. (1997), and Easton/Dennis (1967). Think
hard about their theories and hypotheses.
Worksheet 5 is due Monday, February 28.
February 28: Paper identifying your research problem and discussing 3 related journal articles is due.
F. Random Sampling and Survey Research (March 2 & 7)
Read: Corbett and
Shively, Ch. 7, pp. 97-102.
Worksheet 6 is due Monday, March 7.
MIDTERM EXAM: Wednesday, March 9
SPRING BREAK: Week of March 14
Part II: Data Analysis and Statistics
A. Descriptive (Univariate) Statistics (March 21, 23 & 28)
Read: Corbett and LeRoy, Ch. 7-8.
Worksheet 8 is due (Worksheet 7 is not assigned)
B. Bivariate Analysis with Categorical Data Using Crosstabs (March 30, April 4)
Read: Corbett and LeRoy, Ch. 9.
Worksheet 9 is due
C. Statistical Significance Tests and Measures of Association (April 6, 11, 13, 18)
Read: Corbett and LeRoy, Ch. 10
Worksheet 10 is due
April 18: Brief paper outlining and discussing plans for your original data analysis is due.
D. Controlling for Antecedent Variables with Crosstabs (April 20, 25)
Read: Corbett and LeRoy, Ch. 12.
Review Easton and Dennis article.
Worksheet 12 is due (Worksheet 11 is not assigned)
E. Bivariate Analysis with Continuous Data: Correlation and Regression (April 27, May 2 & 4)
Read: Corbett and LeRoy, Ch. 13.
Review articles previously assigned that have used regression analysis.
Worksheet 13 is due
May 2: The final report on your original data analysis is due.
FINAL EXAM: Monday, May 9