There are two basic methods courses in sociology: Sociology 10 (Quantitative Analysis of Social Data) and Sociology 11 (Research Methods). Each course provides a broad overview of how sociologists ask and answer research questions, and provides students with hands-on experience doing sociological research.
In addition, there is an intermediate methods course: Sociology 54 (Chasing the [Causal] Dragon — Intermediate Quantitative Data Analysis for Sociologists).
10. Quantitative Analysis of Social Data
11. Research Methods
54. Change, Context, and Causality: Intermediate Quantitative Data Analysis for Sociologists
For the most up-to-date listing of when each course will be offered, please see the Courses by Term section
SOCY 10 focuses on the statistical methods that sociologists use with quantitative data. This course is designed to introduce students to the logic of statistical analysis and help students gain an awareness of the many uses of statistics in everyday life, and become informed consumers of statistics. Over the course of the term, students will work together to develop a research project and will learn to analyze, collect, and interpret social statistics.
SOCY 11 is designed to provide students with the practical tools of doing social science research and the theoretical background for critiquing and designing research on social issues. We focus specifically on qualitative methods, engaging in a wide range of methods throughout the term—including interviewing, content analysis, and ethnographic observations—and enabling students to design a research project addressing specific and testable questions.
Both courses focus on developing the skills necessary to interpret, critique, and conduct social science research.
This course provides an introduction to the methods and statistical techniques of quantitative analysis. The first part of the course deals with the methods of quantitative analysis (research design, conceptualization, operationalization, and measurement). The second part of the course introduces students to parametric and nonparametric statistics (frequency distributions, cross tabulations, measures of association, tests of significance, correlation, and bivariate regression). There is a strong emphasis in this course on applying the methods and techniques learned to actual social science data. No previous statistical or advanced mathematical training is assumed, but solid arithmetic and basic algebraic skills are necessary. Because of the large overlap in material covered, no student may receive credit for more than one of the courses: Economics 10, Government 10, Mathematics 10, Psychology 10, Quantitative Social Science 15 or Sociology 10 by special petition. Dist: QDS.
(course syllabus) Rogers
McCabe
This course is designed to provide students with the practical tools of doing social science research and the theoretical background for scientific inquiry into social issues. In the first part of the course we will discuss the research process itself, as well as conceptual issues in theory building and hypothesis testing. In the second part, students will devise and carry out group and individual research projects around a substantive topic. Each project will involve a variety of research techniques, the exact use and applicability of which will be the topic of class discussions. In addition, we will discuss ethical issues and the relevance of social science research for policy making and for advocacy. Dist: SOC.
Sociologists and other social scientists are often interested in understanding causal and dynamic social processes such as: "How do the places we live, work, and play get under the skin and affect health and well-being across the life course?" "Does upward social class mobility change one's political attitudes?" "What social currents are responsible for changes in support for same-sex marriage across historical time?" "Are long-standing racial inequalities declining, persisting, or increasing in recent years?" Many of these questions are methodologically difficult to answer with observational (non-experimental) data, and they require that we get a handle on the study of change, context, and causality. You likely have learned how to answer questions like these with standard OLS (linear) regression techniques and cross-sectional data, which remain useful tools in social scientists' methodological toolbox. But these techniques are also quite limited, and impose strict assumptions that do not allow us to meet many of our goals, adequately answer our questions, or provide stringent tests of our theories and hypotheses. In this course, we'll pick up where introductory statistics courses leave off, and get an introduction to more advanced statistical methods for observational data, including but not limited to: regression for categorical dependent variables, fixed and random effects models, and hierarchical linear modeling. This course will be a mix of seminar and lecture, where we will be focused on understanding how we can use these methods to better meet our goals and answer our research questions. Put differently, this course is less focused on going "under the hood" and more focused on "how to drive"—specifically, we will interrogate the assumptions and use of these statistical methods in the social sciences and learn how to implement these methods using STATA. This will include: discussion of core methodological assumptions and limitations, how to apply these statistical methods in different settings, and learning when specific methods are appropriate tools and when they are not. We will explore these issues through student-led discussions, hands-on data analysis, and dissecting the application of these methods in academic journal articles. As part of this course, you will be exposed to (and critique) a wide range of sociological research published in our major disciplinary journals. The course will culminate in an independent research project where students will analyze data and use the one or more of the modeling techniques discussed during the term to answer a sociological research question of their choosing.