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:
Potential alternative to SPSS: PSPP software: 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 the authors' claims are correct (and if they can avoid lawsuits from IBM, the makers of SPSS), 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. This may be downloaded freely for Mac, Windows, and Linux platforms:
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.
Exam 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)
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 (due Feb. 5)
- Homework #3 (due Mar. 5.) Note that this requires you to analyze one of the following two articles:
- Travis J. Baker (2016). "Delayed Gratification: Party Competition for White House Control in the U.S. House of Representatives." Political Research Quarterly 69, 3 (September): 457-468.
- Mehmet Gurses (2015). "Transnational Ethnic Kin and Civil War Outcomes." Political Research Quarterly 68, 1 (March): 142-153.
- Homework #4 (due Mar. 23) Note that this requires you to use SPSS (or PSPP) to analyze the following data set:
- States.sav data set (the SPSS data set that is used for the last three homework assignments, compiled by the author of our textbook)
- Homework #5 (due Apr. 25) Note that this requires you to use SPSS (or PSPP) to analyze the same data set that was used for Homework 4.
- Homework #6 (due May 2) Note that this requires you to use SPSS (or PSPP) to analyze the same data set that was used for Homework 4.
Using SPSS Software
SPSS statistical software ("Statistical Package for the Social Sciences") 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. This document offers a brief introduction to SPSS and guidelines on how to use it for this course's homework assignments. Note that this will be a work in progress, with more guidelines and instructions being added later in the semester as later assignments require additional statistical techniques, and I will eventually add material that won't be required this semester but could be very helpful if you ever use SPSS for future research, coursework, or employment (such as reading in raw data, formatting and recoding data, and using SPSS syntax files rather than just using the dropdown menus).
- My SPSS Guidelines and Instructions (Last updated 10 March 2018 - added more details about PSPP, opening files, and using the dictionary rather than codebook to display variable information)
These additional online resources go into more detail about some of the techniques and options that we will be using in this course's homeworks, as well as many of the techniques and options available in SPSS that we will not be using this semester but that you might need to use later:
- SPSS Manuals (more detail on what each command does and what options are available)
- Online SPSS Tutorials:
- SPSS Tutorial from Kent State University
- SPSS Tutorial from NC State
- SPSS Tutorials from UCLA
- SPSS Tutorials from UNT
- SPSS Tutorials from UT-Austin
- SPSS Tutorials from Wisconsin: The Basics and Statistics and Graphs
- Student Guide to SPSS (from Dan Flynn at Barnard College)
- Philip H. Pollock III (2015), IBM SPSS Companion to Political Analysis, 5th edition. (A book about using SPSS that is intended as a companion to the textbook)
Potential alternative to SPSS, PSPP software: As mentioned in class, after the start of the Spring 2018 semester, I became aware of a free statistical package called PSPP that claims to be just about identical to SPSS (at least for the relatively basic statistical techniques that we are using in this course). I make no guarantee that this will work, and it is too late to rework all of the assignments this semester to use PSPP rather than SPSS, but this material is included here in case students wish to test it and see if it will work for them.
- PSPP Manual (more detail on what each command does and what options are available)
- PSPP FAQs
- Online PSPP Tutorials:
- Basic Stats in PSPP (from Norm Lewis of the University of Florida)
- PSPP Tutorial (from NC State University)
- Jagnasu Yagnik (2014), "PSPP: A Free and Open Source Tool for Data Analysis." Voice of Research 2, 4 (March): 73-76. (An online article summarizing the capabilities of PSPP version 0.8.1 -- note that the software has advanced since then, so portions of this article may be out of date now, but it is still a useful introduction.)
Additional Resources
These resources are not required for the class, but some students may find them interesting or helpful if they end up using quantitative methods in their own research after this semester.
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, various editions. Sage/CQ Press. (The book that I am currently using for this course)
- Craig Leonard Brians, Lars Willnar, Jarol B. Manheim, and Richard C. Rich, Empirical Political Analysis, various editions. Routledge/Taylor and Francis. (A book that a number of my colleagues have used over the years. This book does a good job of covering a lot of material, but it is also quite pricey, at nearly three times the cost of the Pollock book.)
- Janet Buttolph Johnson, H.T. Reynolds, and Jason D. Mycoff. Political Science Research Methods, various editions. 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, various editions. (a little more advanced than Pollock or Johnson et al., but a very good book)
Less Advanced Statistics Books (less mathematical, often aimed at the general public)
- Larry Gonick and Woollcott Smith (1993). The Cartoon Guide to Statistics. New York: HarperPerennial.
- Charles Wheelan (2014). Naked Statistics: Stripping the Dread from the Data. W. W> Norton.
More Advanced Statistics Textbooks (typically require more math background, aimed at grad students and professionals)
- William H. Greene. Econometric Analysis, various editions. Pearson/Prentice-Hall.
- Damodar Gujarati. Basic Econometrics, various editions. New York: McGraw-Hill.
- Peter Kennedy. A Guide to Econometrics, various editions. Blackwell Publishing.
- Gary King (1989). Unifying Political Methodology: The Likelihood Theory of Statistical Inference. Cambridge: Cambridge University Press.
- G. S. Maddala (1983). TLimited-Dependent and Qualitative Variables in Econometrics. Cambridge: Cambridge University Press.
Mathematical Review
- Jeff Gill (2006). Essential Mathematics for Political and Social Research. Cambridge: Cambridge University Press.
- Will H. Moore and David A. Siegel (2013). A Mathematics Course for Political and Social Research. Princeton, NJ: Princeton University Press.
- Relevant Titles from Sage QASS Series:
- John Fox (2008). A Mathematical Primer for Social Scientists
- Timothy M. Hagle (1995). Basic Math for Social Scientists: Concepts
- Timothy M. Hagle (1996). Basic Math for Social Scientists: Problems and Solutions
- Gudmund R. Iversen (1996). Calculus
- Krishnan Namboodiri (1984). Matrix Algebra: An Introduction
Thinking Scientifically
- Hubert M. Blalock, Jr. (1984). Basic Dilemmas in the Social Sciences. Newbury Park, CA: Sage.
- John L. Casti (1990). Searching for Certainty: What Scientists Can Know about the Future. New York; William Morrow and Company.
- A.F. Chalmers (1999). What Is This Thing Called Science, 3rd edition. Indianapolis: Hackett Publishing.
- Cynthia Crossen (1994). Tainted: The Manipulation of Fact in America. New York Touchstone.
- Jordan Ellenberg (2014). How Not to Be Wrong: The Power of Mathematical Thinking. New York: Penguin.
- Steve D. Levitt and Stephen J. Duber (2006). Freakonomics: A Rogue Economist Explains the Hidden Side of Everything. William Morrow Publishers.
- John Allen Paulos (1995). A Mathematician Reads the Newspaper. New York: Basic Books.
- Arthur L. Stinchcombe (1968). Constructing Social Theories. Chicago: University of Chicago Press.
- Stephen Van Evera (1997). Guide to Methods for Students of Political Science. Ithaca: Cornell University Press.
Research Design
- Henry E. Brady and David Collier, eds. (2004). Rethinking Social Inquiry: Diverse Tools, Shared Standards. Lanham, MD: Rowman and Littlefield.
- Hubert M. Blalock, Jr. (1964). Causal Inferences in Nonexperimental Research. Chapel Hill: University of North Carolina Press.
- John W, Creswell (1994). Research Design: Qualitative and Quantitative Approaches. Thousand Oaks, CA: Sage.
- Gary Goertz (2006). Social Science Concepts: A User's Guide. Princeton: Princeton University Press.
- Gary King, Robert O. Keohane, and Sidney Verba (1994). Designing Social Inquiry. Princeton, NJ: Princeton University Press.
- Relevant Titles from Sage QASS Series:
- Valentin R. Alfares (2012), Methods of Randomization in Experimental Design
- Steven R. Brown and Lawrence E. Melamed (1990), Experimental Design and Analysis
- James A. Davis (1985), The Logic of Causal Order
- Irwin P. Levin (1999), Relating Statistics and Experimental Design: An Introduction
- Scott Menard (2002), Longitudinal Research, 2nd edition
- Paul E. Spector (1981), Research Designs
Case Studies and Comparative Method
- Harry Eckstein (1975). "Case Study and Theory in Political Science." In Fred Greenstein and Nelson Polsby (eds), Handbook of Political Science vol.7. Addison Wellsley.
- Alexander George and Andrew Bennett (2004). Case Studies and Theory Development in the Social Sciences. Cambridge, MA: MIT Press.
- John Gerring (2007). Case Study Research: Principles and Practices. Cambridge: Cambridge University Press.
- Adam Przeworski and Henry Teune(1970). The Logic of Comparative Social Inquiry. Malabar, FL: Robert E. Krieger Publishing Company.
- Charles C. Ragin (1987). The Comparative Method: Moving beyond Qualitative and Quantitative Strategies. Berkeley: University of California Press.
- Robert K. Yin (2017). Case Study Research and Applications: Design and Methods. Sage. (see also earlier editions published as Case Study Research: Design and Methods)
- Relevant Titles from Sage QASS Series:
- Daniele Caramani (2008), Introduction to the Comparative Method with Boolean Algebra
Concepts and Measurement
- Relevant Titles from Sage QASS Series:
- Edward G. Carmines and Richard A. Zeller (1979), Reliability and Validity Assessment
Using Quantitative Data
- Relevant Titles from Sage QASS Series:
- Paul D. Allison (2001), Missing Data
- Herbert Jacob (1984), Using Published Data: Errors and Remedies
Collecting Your Own Data
- Relevant Titles from Sage QASS Series:
- Randy Hodson (1999), Analyzing Documentary Accounts
Survey Data
- Relevant Titles from Sage QASS Series:
- Orlando Behling and Kenneth S. Law (2000), Translating Questionnaires and Other Research Instruments
- Linda B. Bourque and Virginia A. Clark (1992), Processing Data: The Survey Example
- Jean M. Converse and Stanley Presser (1986), Survey Questions: Handcrafting the Standardized Questionnaire
- Glenn Firebaugh (1997), Analyzing Repeated Surveys
- K. Jill Kiecolt and Laura E. Nathan (1985), Secondary Analysis of Survey Data
- Eun Sul Lee and Ronald N. Forthofer (2005), Analyzing Complex Survey Data
Political Science Research Skills
- Lisa A. Baglione (2012), Writing a Research Paper in Political Science. Washington, DC: Sage/CQ Press.
- Leanne C. Powner (2015), Empirical Research and Writing. Washington, DC: Sage/CQ Press.
Descriptive Statistics
- Relevant Titles from Sage QASS Series:
- Frederick Hartwig and Brian E. Dearing (1979), Exploratory Data Analysis
- William G. Jacoby (1997), Statistical Graphics for Univariate and Bivariate Data
- William G. Jacoby (1998), Statistical Graphics for Visualizing Multivariate Data
- Michael Lewis-Beck (1995), Data Analysis: An Introduction
- Herbert F. Weisberg (1991), Central Tendency and Variability
Sampling and Inferential Statistics
- Relevant Titles from Sage QASS Series:
- Tamas Rudas (2004), Probability Theory: A Primer
- Michael J. Smithson (2002), Confidence Intervals
Hypothesis Testing
- Relevant Titles from Sage QASS Series:
- Ramon E. Henkel (1976), Tests of Significance
- Lawrence B. Mohr (1990), Understanding Significance Testing
Measures of Association
- Relevant Titles from Sage QASS Series:
- Peter Y. Chen and Paula M. Popovich (2002), Correlation: Parametric and Nonparametric Measures
- Jean D. Gibbons (1992), Nonparametric Statistics: An Introduction
- Jean D. Gibbons (1993), Nonparametric Measures of Association
- Frederick Hartwig and Brian E. Dearing (1979), Exploratory Data Analysis
- David K. Hildebrand, James D. Laing, and Howard L. Rosenthal (1977), Analysis of Ordinal Data
- 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
- Tamas Rudas (1997), Odds Ratios in the Analysis of Contingency Tables
Regression Analysis
- William D. Berry and Mitchell S. Sanders (2000), Understanding Multivariate Research: A Primer for Beginning Social Scientists
- Relevant Titles from Sage QASS Series:
- Christopher H. Achen (1982), Interpreting and Using Regression
- Paul D. Allison (2009), Fixed Effects Regression Models
- Robert Andersen (2007), Modern Methods for Robust Regression
- William D. Berry (1993), Understanding Regression Assumptions
- William D. Berry and Stanley Feldman (1985), Multiple Regression in Practice
- John Fox (1991), Regression Diagnostics: An Introduction
- Damodar N. Gujarati (2018), Linear Regression: A Mathematical Introduction
- Rpbert L. Kaufman (2013), Heterskedasticity in Regression
- Larry D. Schroeder, David L. Sjoquist, and Paula E. Stephan (2016), Understanding Regression Analysis: An Introductory Guide, 2nd edition
- Colin Lewis-Beck and Michael S. Lewis-Beck (2015), Applied Regression: An Introduction, 2nd edition
- Melissa A. Hardy (1993), Regression with Dummy Variables
- James Jaccard and Robert Turrisi (2003), Interaction Effects in Multiple Regression>, 2nd edition
Logit/Probit and Related Methods
- David W. Hosmer and Stanley Lemeshow (2000), Applied Logistic Regression, 2nd edition. New York: Wiley-interscience.
- David G. Kleinbaum (1994), Logistic Regression: A Self-Learning Text. New York: Springer.
- Relevant Titles from Sage QASS Series:
- John H. Aldrich and Forrest D. Nelson (1984), Linear Probability, Logit, and Probit Models
- Alfred DeMaris (1992), Logit Modeling: Practical Applications
- Scott R. Eliason (1993), Maximum Likelihood Estimation: Logic and Practice
- James J. Jaccard (2001), Interaction Effects in Logistic Regression
- Tim Futing Liao (1994), Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models
- Scott W. Menard (2001), Applied Logistic Regression Analysis
- Fred C. Pampel (2000), Logistic Regression: A Primer
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; the more advanced statistics textbooks listed above often cover many of these topics as well.
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)
- Janet M. Box-Steffensmeier and Bradford S. Jones (2004). Event History Modeling: A Guide for Social Scientists. Cambridge: Cambridge University Press.
- David W. Hosmer and Stanley Lemeshow (1999). Applied Survival Analysis: Regression Modeling of Time to Event Data. New York: John Wiley and Sons.
- David G. Kleinbaum (1996). Survival Analysis: A Self-Learning Text. New York: Springer.
- Tony Lancaster (1990). The Econometric Analysis of Transition Data. Cambridge: Cambridge University Press.
- Kazuo Yamaguchi (1991). Event History Analysis. Newbury Park, CA: Sage.
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)
- David McDowall, Richard McCleary, Errol Meidinger, and Richard A. Hay, Jr. (1980), Interrupted Time Series Analysis (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.
Political Polls
- 538's Politics section (a web site focused on polling and scientific approaches to common questions)
- Pollster ratings (summaries of how major polls work, with ratings of their methodology and accuracy
- Gallup presidential approval poll
- Poll methodology (see also their broader Methodology center)
- State of the States (state-level polling data)
- Other political polls
- Pew Research Center polls
- Survey methodology
- Specific polling topics: U.S. politics, Religion and public life, Social trends, Global polls
- RealClearPolitics polling data (access to the results of current political polls from many different sources)
- U.S. Presidential Approval data and other polling data (from the Roper Center for Public Opinion Research at Cornell University)
Survey Data
- Afrobarometer (survey data from 37 African countries)
- American National Election Studies (ANES) data center (data and documentation for all ANES surveys dating back to 1948)
- 2016 survey methodology (note that earlier surveys may have used different methods, so be sure to check the survey page in the Data Center linked above to see how any given survey was run
- ANES Guide to Public Opinion and Electoral Behavior (track poll results over time for repeated questions, some dating back to 1948)
- Eurobarometer survey archive (survey data from European countries)
- General Social Survey (GSS) data archive (data and documentation for GSS surveys dating back to 1972)
- 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)
- World Values Survey (survey data covering close to 100 countries).
Widely Used Data Sets
- Correlates of War (COW) project data archive
- 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)
- Peace Research Institute of Oslo (PRIO) data archive
- Polity IV political data archive (from the Center for Systemic Peace - scroll down to find the Polity data)
- U.S. Census Bureau data
http://www.paulhensel.org/Teaching/psci2300.html
Last updated: 11 April 2018
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