Lecturer
Thomas Chadefaux
Room: 5.05 (College Green)
Office hours: By Appointment
Tutor
Andrea Salvi
Module Description and Objectives
This module explores a variety of both qualitative and quantitative social science research to develop the skills for explaining causal mechanism in political phenomena. Especially, the class focuses on the logic of scientific inference, research design and measurement. This module also explores the uses and abuses of statistical reasoning in social and political studies. Students learn the basic rules of data analysis and the logic of statistical inference. The class covers various topics such as survey methodology, content analysis, (quasi) experiments, and policy analysis by doing such work themselves.
On successful completion of this module students should be able to:
Critically analyse existing political science and social science research on the basis of the research methods employed.
Specify appropriate research questions in political science and construct effective research design strategies to answer these questions.
Analyse quantitative data to uncover relationships between theoretically relevant variables.
Effectively use statistical methods to conduct political science research.
Effectively employ SPSS, a statistical software package, to conduct political science research.
Lectures
We will have per week:
Tuesdays: 14-15 (M20 in the Museum Building)
Wednesdays: 14-15 (Regent House)
Typically, one of the lectures will be about research methods in general, while the other will focus on statistical methods. The lectures will add to the readings for each week by providing (political science) examples, highlighting the main points, explaining difficult concepts and methods and providing extra material which is not covered in the textbooks or additional readings.
Tutorial Sessions
The tutor for this class is Andrea Salvi. Participation in tutorial sessions is mandatory. It will be very difficult to do well on homework assignments, papers or the final exam if you do not attend tutorials regularly. Tutorials provide a forum for going over homework, similar problem sets, and topics covered in the lecture. The tutorials will also introduce the statistical software necessary to complete the assignments. Please note that it is necessary to be well prepared during tutorials (reading assigned materials, attending lectures, doing homework). The tutor will not repeat what is in the book or what was covered in the lecture. We assume that you have done that. The only way to learn methods and statistics well is by practising, so make sure to prepare your homework exercises well.
We will have weekly tutorial sessions from week 3 on. You will be assigned to a tutorial group automatically. Once you are assigned, you can only attend that group’s meetings unless you receive permission from the tutor to switch groups (either permanently or for a single session).
Contacting us
The first point of contact is the tutor. If there is a practical matter which requires the attention of the lecturer, you may contact us by e-mail, but note that we will respond only during normal office hours (and do not expect an immediate response).
When you have substantive questions about what we are covering in the course, please save up your questions for the Q\(\&\) A during the lecture and for the tutorial group meetings. You can also visit the lecturer’s office hours, but note that we expect that you will have attended the lecture and tutorial groups and done the homework first. Office hours are not intended to replace the lectures and tutorial groups. As a rule, we will not deal with substantive questions via e-mail.
Blackboard
I will provide module announcements via Blackboard. Moreover, all homework and paper assignments will be made available there.
If you are registered for this module in My TCD, you should also be automatically added to the Blackboard environment. Please make sure this is indeed the case.
Literature
We will use the following text books in the module:
Manheim, J.B., R.C. Rich, L. Wilmat, C.L. Brians and J. Babb (2012) Empirical Political Analysis: An Introduction to Research Methods. Harlow: Pearson Education. ISBN: 1408204622
Field, A. (2013) Discovering Statistics Using SPSS. 4th edition (3^{rd} edition may also be used, but relevant parts from the fourth edition should be obtained elsewhere). London: Sage.
It is essential that you acquire your own copy of Manheim et al. (2012), because we will read almost all of it. We will read only about half of Field (2013), but it is recommended that you get your own copy as it is a good reference book. Make sure that you have access to the chapters that we will be using in class.
In addition, we will use a number of journal articles and book chapters. Most journal articles will be freely available from the link included in the reading list (from campus computers). If this does not work (or if you are not on campus), search for the article via Stella Search (or Google Scholar) and log in to gain access.
SPSS
We will use the statistical software package IBM SPSS Statistics (version 21, version 22 can also be used) in this module. It is imperative that you install this on your computer . Please refer to IS Services how to obtain your free copy: http://isservices.tcd.ie/software/kb/student_software.php
Grading
The final grade consists of the following parts:
60\(\%\) of the mark is based on an end-of-term exam, which covers both research methods and statistics. The exam will consist of short descriptions of relevant concepts, short essay questions and the interpretation of a statistical model. A sample exam can be found here.
1 paper counting 16\(\%\) towards your overall mark. In this paper, you will set up a (small) research project (based on secondary data) and execute it (including a limited statistical analysis). This work will be done in groups submitting joint papers. We will assign you to a random partner for this project. Further information on the paper assignment will be made available via Blackboard. The deadline for submitting the paper on Turnitin is Friday, November 29, 23:59. Only one of the co-authors should submit the paper, but be sure to indicate the other co-authors on the title page.
Details on the papers and what we expect can be found here
Details on the presentations and what we expect can be found here
Homework exercises are worth 20\(\%\) of your overall mark. In total, students will complete 4 of these exercises. These homework exercises must be submitted on Turnitin (via Blackboard).
Tutorial participation is worth 4\(\%\) of your overall mark. Students should present themselves at their tutorials and be prepared to discuss their work in class. They should also attend the presentation sessions (weeks 9 and 10 in lecture). Two unexcused absences in tutorials and 1 in the presentation will be tolerated. Beyond that, the student will receive a zero for participation.
Late Submissions
5 points per day will be taken off your mark on assignments submitted late without a valid excuse (capped at 30 points).
Plagiarism
Unless explicitly stated otherwise, all coursework is individual and should be original (you should re-use parts of a paper you wrote for another module, for example).
You need to reference any literature you use in the correct manner. This is true for use of quotations as well as summarizing someone else’s ideas in your own words. Useful information regarding essay writing may be found in the political science undergraduate student handbook, as well as http://www.plagiarism.org.When in doubt, consult with the lecturer before you hand in an assignment. Plagiarism is regarded as a major offence that will have serious implications.
Paper Submission
All coursework must be submitted on Turnitin via mymodule.tcd.ie.
All coursework deadlines are strictly adhered to. Extensions on deadlines will only be granted in exceptional circumstances; relevant documentation (for example a medical certificate, or a letter/e-mail from your college tutor explaining the circumstances) should be provided when an extension is requested. All late work, unless excused beforehand, will have 5 marks deducted for each day beyond the deadline, as stated in the political science undergraduate student handbook.
The weekly homework exercises must be submitted through turnitin on the Monday evening (11:59pm) preceding the tutorial session. This applies regardless of the tutorial you are assigned to. Attendance records are based on: 1) your presence at tutorial and 2) proof that the homework was attempted by the deadline. Please make sure that your answers are typed into a Word document and that you have made a good faith attempt at the analyses. Screenshots of the SPSS output is not sufficient—you will need to interpret the results and procedures.
Week 1
Methods Lecture: Why do I need to learn about research methods?
Readings: Manheim et al., Chapter 1
Statistics Lecture: Why statistics? The problem of sampling
Readings: Field, Chapter 1 (1.1 to 1.5 including)
Week 2
Methods Lecture: Theories & concepts
Readings:
Manheim et al., Chapter 2 and 3
Gerring, J. (1999). What Makes a Concept Good? A Criterial Framework for Understanding Concept Formation in the Social Sciences. Polity, 31(3), 357:393.
Statistics Lecture: Univariate statistics: Measurement levels and measures of central tendency
Readings:
Week 3
Methods Lecture: Variables, hypotheses & measurement
Readings: Manheim et al., Chapter 4
Statistics Lecture: Univariate statistics: Measures of dispersion and standard errors
Readings:
Week 4
NOTE: HOMEWORK 1 DUE (submit on Turnitin)
Methods Lecture: Measurement error and the research plan
Readings: Manheim et al., Chapter 5
Statistics Lecture: Univariate statistics: confidence intervals & significance testing
Readings: Field, Chapter 2 (section 2.5.2 to 2.13)
Week 5
Methods Lecture: Qualitative vs. quantitative research?
Readings:
Statistics Lecture: Presenting data: tables and charts
Readings:
Week 6
NOTE: HOMEWORK 2 DUE (submit on Turnitin)
Statistics Lecture (no “methods” this week): Bivariate statistics: cross tables and chi-square
Readings: Manheim et al., Chapter 17
Statistics Lecture: Catch-up on late lectures
Week 7: STUDY WEEK
Week 8
Statistics Lecture: Bivariate statistics: correlation
Readings: Field, Chapter 7
Statistics Lecture: Bivariate statistics: t-tests
Readings: Field, Chapter 9
Week 9
NOTE: HOMEWORK 3 DUE (submit on Turnitin)
Tuesday: Presentations
Wednesday: Presentations
Week 10
Tuesday: Presentations
Wednesday: Presentations
Week 11
Methods Lecture: Experimental research
Readings:
Methods Lecture (no statistics this week): From experimental to quasi-experimental research
Readings:
Week 12
NOTE: HOMEWORK 4 DUE (submit on Turnitin)
Methods Lecture: Formal analysis and rational choice
Readings: Osborne, M. J. (2003). An Introduction to Game Theory. Oxford: Oxford University Press. Chapter 1 & 2 available from http://www.economics.utoronto.ca/osborne/igt/intro.pdf and http://www.economics.utoronto.ca/osborne/igt/nash.pdf
Wednesday: Q&A, recap
FRIDAY 29/11, 23:59: Final Paper due