POS 2300: Introduction to Political Science Research |
Dr. Paul Hensel |
Please note that this web page does not include the full syllabus for this course. The remainder of the syllabus -- most notably the schedule of assigned readings, course exams, and other assignments -- is only available in the full syllabus (in PDF format). Be sure to print out that complete syllabus and be familiar with it, so that you do not fall behind or miss any assignments during the semester.
Course Description
The primary purpose of this course is to introduce students to the methods and terminology used by social scientists. We will examine basic concepts used in research (such as theories, hypotheses, independent and dependent variables, reliability and validity, and sampling). We will also examine basic statistical techniques that are used to examine data, with an emphasis on interpreting the results (ranging from descriptive statistics to crosstabs, correlation, and regression). Upon completion of this course, students should be able to understand and interpret most research published in political science journals, as well as public opinion polls, surveys, and research findings reported in the news. As a result, students who complete this course should be prepared for future coursework in the social sciences, as well as for a life as an educated and informed citizen.
Students are expected to finish the course readings before the class period for which they are assigned, attend class regularly (showing up to class on time and staying through the end), and participate actively in class discussion where relevant. The course will be graded using three examinations (two midterms and a final) and six homework assignments (several of which will require the use of SPSS statistical software).
Required Texts
Book: This should be available at the usual Denton locations, or maybe cheaper through online bookstores -- but wherever you buy it, be sure to get the correct edition!
- Philip H. Pollock III (2016). The Essentials of Political Analysis, 5th ed. Sage/CQ Press.
Blackboard: The remaining readings are available online through the Blackboard page for this course, which you can access by using your EUID to log in at https://learn.unt.edu.
SPSS software: Some of the homework assignments toward the end of the semester will require the use of SPSS statistical software, which is installed in many UNT computer labs. If you are interested in getting your own copy of SPSS rather than depending on computer labs, you may order it through UNT at a substantial student discount. You will need the "SPSS Statistics" version of the SPSS Grad Pack, which is available for both Mac and Windows at a cost of $58.99 (6 month rental) or $86.99 (12 month rental) at the following site:
Course Requirements
(1) Examinations: Three (noncumulative) exams are required. The exams will involve a mixture of questions to measure understanding of the wide variety of material covered in this course, including some multiple choice and some short answer (some requiring the interpretation of results and others requiring calculations). Each exam will be worth 25% of the total course grade.
(2) Homework Assignments: There is no better way to learn concepts than through hands-on experience. There will be six (6) homework assignments, which will each be handed out one week before the due date. Together, these assignments will be worth 25% of the total course grade; each student's lowest homework grade will be dropped.
Be aware that the course rules require completing all assignments in order to receive a non-failing grade for the course, so you must turn in at least five of the six homework assignments to pass the course (if you only turn in five the sixth would count as the lowest score being dropped).
(3) Preparation and Attendance: An important part of a course like this is making sure that students understand the concepts as the semester is moving along. The best way to do this is to attend class regularly, having done the assigned readings beforehand (trying to cram a month's worth of reading, or xeroxing a classmate's notes from the entire semester, a few days before an exam is rarely a good strategy). Class preparation and attendance will not be graded directly, but students are expected to prepare for class and attend regularly, and failure to do so will almost certainly be reflected in one's performance on exams and homework.
Rest of Syllabus
The remainder of the syllabus -- course rules, notes about the academic honor code and the Americans with Disabilities Act, and assigned readings -- is only available in the complete syllabus (in PDF format). Be sure to print out that complete syllabus and be familiar with it, so that you do not fall behind or miss any assignments during the semester.
Homework Assignments
Each homework assignment will be posted here when it becomes available (do not bother checking before the date when it is handed out, because these will not be posted early):
- Homework #1 (survey handed out and completed in class on Jan. 24)
- Homework #2 (handed out Jan. 29, due Feb. 5)
- Homework #3 (handed out Feb. 26, due Mar. 5)
- Homework #4 (handed out Mar. 7, due Mar. 19)
- Homework #5 (handed out Apr. 18, due Apr. 25)
- Homework #6 (handed out Apr. 25, due May 2)
Review Sheets
Review sheets will be posted here one week before each exam, to help students prepare for the exams (do not bother checking before the date when it is handed out, because these will not be posted early):
- Review for Exam #1 (exam on Feb. 16, review handed out Feb. 9)
- Review for Exam #2 (exam on April 4, review handed out Mar. 28)
- Review for Final Exam (exam on May 9, review handed out May 2)
SPSS Software
Some of the homework assignments toward the end of the semester will require the use of SPSS statistical software. This software is used in many academic settings and many businesses, so experience using it can be very helpful after completing this course. Even if you end up in a discipline or business that uses a different statistical package, the experience of having worked with SPSS will help you make the transition to their preferred software much more easily than if you had never done this.
Obtaining SPSS
SPSS is installed in many UNT computer labs. If you are interested in getting your own copy of SPSS rather than depending on computer labs, you may order it through UNT at a substantial student discount. You will need the "SPSS Statistics" version of the SPSS Grad Pack, which is available for both Mac and Windows at a cost of $58.99 (6 month rental) or $86.99 (12 month rental) at the following site:
Using SPSS
SPSS ("Statistical Package for the Social Sciences") is a widely used statistical package, both in college methods courses and in the professional world, so many places offer tutorials in using it. Note that these tutorials were written using different versions of SPSS and possibly on a different operating system than you use, but for the purposes of this class there shouldn't be any real difference; the basic menu structure of SPSS should be the same on every computer platform, and most of the differences between SPSS versions involve more complex features that are beyond the scope of an introductory course like this.
- SPSS Tutorials from UCLA
- SPSS Tutorials from UNT Office of Research and Statistical Support
- SPSS Tutorials from UT
Possible Alternative: PSPP
After the start of the Spring 2018 semester (i.e., too late to investigate this and possibly change the syllabus), I became aware of a free statistical package called PSPP that is claimed to be very similar to SPSS: "it behaves as experienced SPSS users would expect, and their system files and syntax files can be used in PSPP with little or no modification, and will produce similar results (the actual numbers should be identical)". It is too late for me to rework the syllabus and assignments for the course this semester, but students are welcome to try it themselves if they would like to avoid paying for their own SPSS license or having to go to a campus computing lab. If these claims are correct, PSPP should work just as well as SPSS for the course homeworks -- but because I have not had the time to test it out and potentially revise my assignments or instructions, I make no guarantees that it will work. I will look into PSPP more carefully before I teach this course again.
- PSPP home
- PSPP Manual and FAQs
- Download PSPP (versions are available for the Mac, Windows, and numerous Linux distributions)
- PSPP Tutorial (from NC State University)
Additional Resources
These resources are not required for the class, but some students may find them interesting or helpful.
Greek Letters
Confused by all of the Greek letters used in statistics? This web page offers pictures of both uppercase and lowercase Greek letters, with the name of each letter spelled out and the English equivalent.
Published References
While many students in this course will be satisfied with completing the course and will not want to use quantitative methods in their own careers (at UNT or afterward), others will want to go further with topics covered in this course, perhaps in writing a senior honors thesis or in preparing for graduate school. This is not a definitive list, but these resources might be helpful guides for going further with these methods than we could in this class. Many of these are from Sage Publications' Quantitative Applications in the Social Sciences series, which offers relatively brief (around 80 pages), accessible, and affordable (around $20) discussion of many important topics (these volumes are often consulted by grad students and faculty doing their own research).
Undergraduate Research Methods Textbooks
- Philip H. Pollock III, The Essentials of Political Analysis. Sage/CQ Press. (The book that I am currently using for this course)
- Janet Buttolph Johnson, H.T. Reynolds, and Jason D. Mycoff. Political Science Research Methods. Sage/CQ Press. (I have used this book in the past. This does a good job of covering the material used in this course, and adds far more coverage of various data sources and data collection techniques than we have time for in the course as I currently teach it; a bit pricier than the Pollock book)
- Paul M. Kellstedt and Guy D. Whitten, The Fundamentals of Political Science Research (a little more advanced than Pollock or Johnson et al., but a very good book)
- More Advanced Statistics Textbooks
- (list coming soon)
- Mathematical Review
- John Fox (2008), A Mathematical Primer for Social Scientists (part of Sage QASS series)
- Timothy M. Hagle (1995), Basic Math for Social Scientists: Concepts (part of Sage QASS series)
- Timothy M. Hagle (1996), Basic Math for Social Scientists: Problems and Solutions (part of Sage QASS series)
- Gudmund R. Iversen (1996), Calculus (part of Sage QASS series)
- Krishnan Namboodiri (1984), Matrix Algebra: An Introduction (part of Sage QASS series)
Research Design
- Valentin R. Alfares (2012), Methods of Randomization in Experimental Design (part of Sage QASS series)
- Steven R. Brown and Lawrence E. Melamed (1990), Experimental Design and Analysis (part of Sage QASS series)
- James A. Davis (1985), The Logic of Causal Order (part of Sage QASS series)
- Gary King, Robert O. Keohane, and Sidney Verba (1994). Designing Social Inquiry. Princeton, NJ: Princeton University Press.
- Irwin P. Levin (1999), Relating Statistics and Experimental Design: An Introduction (part of Sage QASS series)
- David McDowall, Richard McCleary, Errol Meidinger, and Richard A. Hay, Jr. (1980), Interrupted Time Series Analysis (part of Sage QASS series)
- Scott Menard (2002), Longitudinal Research, 2nd edition (part of Sage QASS series)
- Paul E. Spector (1981), Research Designs (part of Sage QASS series)
- Case Studies and Comparative Method
- Daniele Caramani (2008), Introduction to the Comparative Method with Boolean Algebra (part of Sage QASS series)
- Eckstein, "Case Study and Theory in Political Science"
- George, “Case Studies and Theory Development”
- Collier, "The Comparative Method: Two Decades of Change"
- Ragin, The Comparative Method
Concepts and Measurement
- Edward G. Carmines and Richard A. Zeller (1979), Reliability and Validity Assessment (part of Sage QASS series)
- Quantitative Data
- Paul D. Allison (2001), Missing Data (part of Sage QASS series)
- Randy Hodson (1999), Analyzing Documentary Accounts (part of Sage QASS series)
- Herbert Jacob (1984), Using Published Data: Errors and Remedies (part of Sage QASS series)
- Survey Data
- Orlando Behling and Kenneth S. Law (2000), Translating Questionnaires and Other Research Instruments (part of Sage QASS series)
- Linda B. Bourque and Virginia A. Clark (1992), Processing Data: The Survey Example (part of Sage QASS series)
- Jean M. Converse and Stanley Presser (1986), Survey Questions: Handcrafting the Standardized Questionnaire (part of Sage QASS series)
- Glenn Firebaugh (1997), Analyzing Repeated Surveys (part of Sage QASS series)
- K. Jill Kiecolt and Laura E. Nathan (1985), Secondary Analysis of Survey Data (part of Sage QASS series)
- Eun Sul Lee and Ronald N. Forthofer (2005), Analyzing Complex Survey Data (part of Sage QASS series)
Descriptive Statistics
- Frederick Hartwig and Brian E. Dearing (1979), Exploratory Data Analysis (part of Sage QASS series)
- William G. Jacoby (1997), Statistical Graphics for Univariate and Bivariate Data (part of Sage QASS series)
- William G. Jacoby (1998), Statistical Graphics for Visualizing Multivariate Data (part of Sage QASS series)
- Michael Lewis-Beck (1995), Data Analysis: An Introduction (part of Sage QASS series)
- Herbert F. Weisberg (1991), Central Tendency and Variability (part of Sage QASS series)
Sampling and Inferential Statistics
- Tamas Rudas (2004), Probability Theory: A Primer (part of Sage QASS series)
- Michael J. Smithson (2002), Confidence Intervals (part of Sage QASS series)
Hypothesis Testing
- Ramon E. Henkel (1976), Tests of Significance (part of Sage QASS series)
- Lawrence B. Mohr (1990), Understanding Significance Testing (part of Sage QASS series)
Measures of Association
- Peter Y. Chen and Paula M. Popovich (2002), Correlation: Parametric and Nonparametric Measures (part of Sage QASS series)
- Jean D. Gibbons (1992), Nonparametric Statistics: An Introduction (part of Sage QASS series)
- Jean D. Gibbons (1993), Nonparametric Measures of Association (part of Sage QASS series)
- Frederick Hartwig and Brian E. Dearing (1979), Exploratory Data Analysis (part of Sage QASS series)
- David K. Hildebrand, James D. Laing, and Howard L. Rosenthal (1977), Analysis of Ordinal Data (part of Sage QASS series)
- Gudmund R. Iversen and Helmut P. Norpoth (1997), Analysis of Variance
- Albert M. Liebetrau (1983), Measures of Association
- H.T. Reynolds (1984), Analysis of Nominal Data (part of Sage QASS series)
- Tamas Rudas (1997), Odds Ratios in the Analysis of Contingency Tables (part of Sage QASS series)
Regression Analysis
- Christopher H. Achen (1982), Interpreting and Using Regression (part of Sage QASS series)
- Paul D. Allison (2009), Fixed Effects Regression Models (part of Sage QASS series)
- Robert Andersen (2007), Modern Methods for Robust Regression (part of Sage QASS series)
- William D. Berry (1993), Understanding Regression Assumptions (part of Sage QASS series)
- William D. Berry and Stanley Feldman (1985), Multiple Regression in Practice (part of Sage QASS series)
- William D. Berry and Mitchell S. Sanders (2000), Understanding Multivariate Research: A Primer for Beginning Social Scientists
- John Fox (1991), Regression Diagnostics: An Introduction (part of Sage QASS series)
- Damodar N. Gujarati (2018), Linear Regression: A Mathematical Introduction (part of Sage QASS series)
- Rpbert L. Kaufman (2013), Heterskedasticity in Regression (part of Sage QASS series)
- Larry D. Schroeder, David L. Sjoquist, and Paula E. Stephan (2016), Understanding Regression Analysis: An Introductory Guide, 2nd edition (part of Sage QASS series)
- Colin Lewis-Beck and Michael S. Lewis-Beck (2015), Applied Regression: An Introduction, 2nd edition (part of Sage QASS series)
- Melissa A. Hardy (1993), Regression with Dummy Variables (part of Sage QASS series)
- James Jaccard and Robert Turrisi (2003), Interaction Effects in Multiple Regression>, 2nd edition (part of Sage QASS series)
Logit/Probit and Related Methods
- John H. Aldrich and Forrest D. Nelson (1984), Linear Probability, Logit, and Probit Models (part of Sage QASS series)
- Alfred DeMaris (1992), Logit Modeling: Practical Applications (part of Sage QASS series)
- Scott R. Eliason (1993), Maximum Likelihood Estimation: Logic and Practice (part of Sage QASS series)
- James J. Jaccard (2001), Interaction Effects in Logistic Regression (part of Sage QASS series)
- Tim Futing Liao (1994), Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models (part of Sage QASS series)
- Scott W. Menard (2001), Applied Logistic Regression Analysis (part of Sage QASS series)
- Fred C. Pampel (2000), Logistic Regression: A Primer (part of Sage QASS series)
Other Methods We Didn't Cover in Class
This section includes other methods that are widely used in social science research, which you may need to understand better, or you may even need to use in your own research. These sources offer a useful starting point.
- Content / Narrative / Textual Analysis
- Robert Philip Weber (1990), Basic Content Analysis (part of Sage QASS series)
- Roberto Franzosi (2009), Quantitative Narrative Analysis (part of Sage QASS series)
- Event History / Survival / Duration Analysis
- Paul D. Allison (2014), Event History and Survival Analysis, 2nd edition (part of Sage QASS series)
- Generalized Linear Models (GLM)
- George H. Dunteman and Moon-ho R. Ho (2005), An Introduction to Generalized Linear Models (part of Sage QASS series)
- Jeff Gill (2000), Generalized Linear Models: A Unified Approach (part of Sage QASS series)
- Richard F. Haase (2011), Multivariate General Linear Models (part of Sage QASS series)
- Geographic Information Systems (GIS) and Spatial Analysis
- G. David Garson and Robert S. Biggs (1992), Analytic Mapping and Geographic Databases, 2nd edition (part of Sage QASS series)
- Michael D. Ward and Kristian Skrede Gleditsch (2018), Spatial Regression Models, 2nd edition (part of Sage QASS series)
- Hierarchical Linear Models (HLM) / Multilevel Modeling
- Douglas A. Luke (2004), Multilevel Modeling, 2nd edition (part of Sage QASS series)
- Multinomial and Ordered Logit/Probit Models
- Vani Kant Borooah (2001), Logit and Probit: Ordered and Multinomial Models (part of Sage QASS series)
- Ann Aileen O'Connell (2005), Logistic Regression Models for Ordinal Response Variables (part of Sage QASS series)
- Neural Network Models
- Herve Abdi, Dominique Valentin, and Betty Edelman (1998), Neural Networks (part of Sage QASS series)
- Selection Models
- Richard Breen (1996), Regression Models: Censored, Sample Selected, or Truncated Data (part of Sage QASS series)
- Time Series Analysis
- Patrick T. Brandt and John T. Williams (2006), Multiple Time Series Models (part of Sage QASS series)
- Jeff B. Cromwell, Walter C. Labys, and Michel Terraza (1993), Univariate Tests for Time Series Models (part of Sage QASS series)
- Jeff B. Cromwell, Walter C. Labys, Michael J. Hannan, and Michel Terraza (1994), Multivariate Tests for Time Series Models (part of Sage QASS series)
- Charles W. Ostrom (1990), Time Series Analysis: Regression Techniques (part of Sage QASS series)
- Mark Pickup (2014), Introduction to Time Series Analysis (part of Sage QASS series)
- Lois Sayrs (1989), Pooled Time Series Analysis (part of Sage QASS series)
Online Data Sources
These sources may be used to download many of the main data sets used by professional political scientists, as well as other sample data sets that might be helpful in learning or applying quantitative techniques.
- Afrobarometer (survey data from 37 African countries)
- American National Election Studies (ANES) data archive (data and documentation for ANES surveys dating back to 1948)
- Correlates of War (COW) project data archive (the leading provider of international relations data)
- Eurobarometer survey archive (survey data from European countries)
- General Social Survey (GSS) data archive (data and documentation for GSS surveys dating back to 1972)
- Historical U.S. Election Results (from the U.S. Electoral College)
- Inter-university Consortium for Political and Social Research (ICPSR) (a huge archive containing data sets from decades of quantitative research in poli sci and the other social sciences)
- Latin American Public Opinion Project (LAPOP) (survey data on 34 Western Hemisphere countries, from Vanderbilt University; includes the AmericasBarometer survey project)
- Latinobarometro survey archive (survey data from 18 Latin American countries)
- Polity IV political data archive (from the Center for Systemic Peace)
- U.S. Census Bureau data
- U.S. Presidential Approval data and other polling data (from the Roper Center for Public Opinion Research at Cornell University)
- World Values Survey (survey data covering close to 100 countries).
http://www.paulhensel.org/Teaching/psci2300.html
Last updated: 16 February 2018
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