IR 211: Approaches to Research
In the Spring of 2013 I am teaching IR 211: Approaches to Research.
This class is an introduction to social science research methodology. My main goal is to teach you the basics of creating and consuming research in the social sciences, and international relations in particular. The course will lead you through conceptualization and theory construction, the derivation of testable hypotheses, and a variety of methodologies that may be used to evaluate these hypotheses. We will discuss causal inference, observation and measurement, and other issues encompassing both qualitative and quantitative research methods. We will discuss the way in which academic articles in the social sciences are written, and how they should be read.
This course includes some very basics statistics, and requires use of Stata (a statistical software package) for some class assignments. These include some simple description and cross tabulation of data from the General Social Survey. Computers with Stata are available in an on-campus computer lab.
The syllabus for the course is here (Updated January 15).
Lecture 1: Introduction
Lecture 2: Social Science Research Overview, Part I
Lecture 3: Social Science Research Overview, Part II
Lecture 6: Research Ethics
Lecture 7: Conceptualization and Measurement (1)
Lecture 8: Conceptualization and Measurement (2)
Lecture 9: Conceptualization and Measurement (3)
Lecture 10: Random Sampling
Lecture 11: Non-Random Sampling
Lecture 12: Art of Causal Inference (1)
Lecture 13: Art of Causal Inference (2)
Lecture 14: Art of Causal Inference (3)
Lecture 15: Experiments (1)
Lecture 16: Experiments (2)
Lecture 17: Survey Research (1)
Lecture 18: Survey Research (2)
Lecture 19: Survey Research (3)
Lecture 20: Qualitative Research Methods (1)
Lecture 21: An Application Exercise
Homework 1 Due Tuesday January 29
Homework 2 Due Tuesday February 19
Homework 3 Due Tuesday, March 12
Homework 4 Due Thursday, April 11
Homework 5 (Part A) Due Thursday May 2
Intention to treat vs. actual treatment. Not everyone in the treatment group always takes the drug (or adheres to the treatment, whatever that might be).
When you read this, think about how the failure to include Spanish tweets affects the sample. How might that omission bias the results?
Data of many types is rapidly increasing in abundance and quality, but a lack of good data is still crippling in many areas of social science, including the study of economic development. For example, we really don't know how economies in Africa are doing.
Vreeland's Goldilocks and the Three Regimes.
Here is more detail on Progresa if you're interested.
Regarding the risks of rigorous outside evaluation, here is the Heritage Foundation using an outside evaluation of the Headstart program to club the program over the head and argue for cutting funding. Here is the outside evaluation itself.
File this under "observation/description/measurement = hard." Even when its something we take for granted, like GDP figures.
Related to Homework 1, here is an opportunity to volunteer counting homeless in LA.