Courses

For official brief descriptions of courses and scheduled instructors, please consult the official Dartmouth course descriptions and requirements published by the Office of the Registrar. For detailed information about the terms and times that courses will be offered, the most reliable source is the Timetable of Class Meetings on the Registrar’s site.

QSS 15

Introduction to Data Analysis

19F: 10

Methods for transforming raw facts into useful information. Directed toward students with an aptitude for mathematics. Emphasis is placed on the understanding, use, and both oral and written interpretation of exploratory data analysis within the rules of scientific method. With permission from the responsible department, QSS 15 may be used to satisfy some pre-medical, natural science, and social science departmental requirements in mathematics, statistics, and methodology.

Prerequisite: Mathematics 3 or higher, or permission. Dist: QDS. Herron.

QSS 17

Data Visualization (Identical to Government 16)

19F, 20S: 10A

Big data are everywhere – in government, academic research, media, business, and everyday life. To tell the stories hidden behind blizzards of data, effective visualization is critical. This course primarily teaches R, a free software environment for statistical computing and graphics, which is widely regarded as one of the most versatile and flexible tools for data visualization and, more broadly, data science. Students completing the course will know how to “wrangle” and visualize data critical to their scientific endeavors.

Dist: TLA. Cooper.

QSS 18

Introduction to Game Theory (Identical to Government 18)

20W: 10

Game theory is used to study how individuals and organizations interact strategically, and this course introduces game theory with a focus on political science applications. Game theory is a standard tool in the social sciences, and insights from game theory are essential to understanding many facets of politics, such as political party competition, legislative politics, international relations, and the provision of public goods. Among other topics, the course will cover normal and extensive form games, Nash equilibria, imperfect information, mixed strategies, and, if time permits, the basics of games with incomplete information. A course in game theory will change that way that one views the world.

Prerequisite: Math 3 or the equivalent. Dist: QDS. Herron.

QSS 30

Special Topics in Quantitative Social Science

This course focuses on a particular topic of interest to students pursuing coursework in quantitative social science. The topics covered by QSS 30 will span economics, political science, sociology, and other fields. The specific topic of the course will change with each offering, and students may therefore take this course more than once.  Please see below for the individual listings.

QSS 30.01

Sports Analytics

19F: 9L

Sports organizations are becoming increasingly aware that analytics are an important component of team success. This course will introduce students to various statistical techniques used in modern sports analysis and in particular will teach participants how statistical methods can be used to analyze game outcomes and evaluate players and strategies.  The course will include lectures, in-class exercises using the R statistical computing environment, and guest speakers from the sports industry. Hanlon and Herron.

QSS 30.02

Computational Text Analysis for the Social Sciences (Identical to MATH 05.01/GOV 19.05)

not currently offered

Language is the medium for politics and political conflict. Candidates debate during elections. Representatives write laws. Nations negotiate peace treaties. Clerics issue Fatwas. Citizens express their opinions about politics on social media sites. These examples, and many others, suggest that to understand what politics is about, we need to know what political actors are saying and writing. This course introduces techniques to collect, analyze, and utilize large collections of text for social science inferences.  Students will also have the opportunity to develop their programming abilities.

We will explore a range of datasets from the text of The Federalist Papers to the millions of tweets sent to and from members of Congress.

Prereq:  Students should have completed GOVT/ECON/PSYC/SOCY/MATH 10 or QSS 15. Dist: TLA. Westwood.

QSS 30.03

Experiments in Politics (Identical to Government 83.21)

19F: 3A, 20S: 2A

This class is a lab-style seminar in which we will design, field, and analyze an experimental study of political misperceptions.  Our goal is to publish a scholarly article about our findings in a peer-reviewed journal of political science-an ambitious project that will require a substantial commitment from each student. Flexibility will also be essential since the course will evolve during the semester based on the needs of the project. Dist: QDS.

QSS 30.04

Evolutionary Game Theory and Applications (Identical to MATH 30.04)

20S: 10A

Pioneered by John Maynard Smith and others, evolutionary game theory has become an important approach to studying a wide range of biological and social problems, such as microbial interactions and animal behavior. In evolutionary game dynamics, the fitness of individuals depends on the relative abundance of all individual types in the population, and higher-fitness individual types tend to increase in abundance. The course introduces basic concepts in evolutionary game theory, including evolutionarily stable strategies, replicator dynamics, finite populations, and games on networks, along with applications to social evolution, particularly to understanding human cooperation.  Dist: QDS (effective 2/2017). Fu.

Prerequisites: Math 3. The student should be familiar with calculus, and basic concepts in ordinary differential equations and probability. Programing skills helpful, but not required.

QSS 30.05

United States History Through Census Data (Identical to History 90.01)

 

This course focuses on using data from historical censuses (1850-2000) to examine U.S. history. We will discuss what the census tells us about the past, the role of the census in policy-making, and the history of the census. The course comprises four units: race, (im)migration, work, and family. For each, you will learn how to find, analyze, and visualize census data using R and how to write about quantitative historical analysis in a digital medium. Dist: QDS. WCult: W. Merchant.

QSS 30.06

By the Numbers: Race, Incarceration, and Politics (Identical to GOVT 19.06)

not currently offered

More than half a century after the height of the Civil Rights Movement, inequalities between black Americans and white Americans persist.  Across a myriad of measures---including health, employment, income, wealth, education, and incarceration---black Americans are fundamentally different than whites. Leveraging contemporary data and modern quantitative techniques, we evaluate black-white racial gaps by the numbers and among other things consider how racial inequalities in the United States might alter the American political landscape. Dist: QDS. Cottrell.

QSS 30.07

Simulating Social Systems: Complexity and Society (formerly The Science of Anarchy: Computational Approaches to Spontaneous Social Order)

not currently offered

In this course we will learn the science and art of "agent-based modeling," the simulation of social phenomena with computer models. Social outcomes seem complex, but that complexity often results from many agents following very simple rules. We will discover the science of spontaneous social order, learning to program in a simple computer language for writing social simulations, and studying models by sociologists, economists, psychologists, political scientists, philosophers, historians, and even computer scientists and physicists.  Dist: SOC. Frey

QSS 30.08

Misperceptions in Politics (Identical to Government 83.09)

 

Many citizens hold misperceptions about political facts. To what extent do misperceptions distort people’s preferences and bias public opinion? This seminar examines the causes and consequences of misperceptions, strategies for correcting misperceptions, and the tools scholars use to study misperceptions scientifically. These tools include surveys, experiments, and a widely used statistical computing program (R). Over the course of the quarter, students will collaborate with the instructor to design, execute, and report an original experimental study of misperceptions. Dist: QDS.

QSS 30.09

Data Wrangling (Identical to QBS 181)

19F: Tu, Th 4:00 PM-5:30 PM 

This course is a survey of methods for extracting and processing data. It will cover data architectures (ontologies, metadata, pipeline and open source resources), database theory, data warehouses, the electronic medical record, various file formats including audio, and video, data security and cloud resources. Students will gain skills working with Big Data using software such as SQL, APACHE Hadoop and Python.

QSS 36

Mathematical Models in the Social Sciences (Identical to Mathematics 36)

19F: 10

Disciplines such as anthropology, economics, sociology, psychology, and linguistics all now make extensive use of mathematical models, using the tools of calculus, probability, game theory, network theory, often mixed with a healthy dose of computing. This course introduces students to a range of techniques using current and relevant examples. Students interested in further study of these and related topics are referred to the courses listed in the Quantitative Social Science program.

Prerequisite: Mathematics 13, 20. Dist: TAS.  DeFord.

QSS 41

Analysis of Social Networks

20S: TBD

Students will gather and analyze data on a variety of networks (institutions, communities, elites, friendship systems, kinship systems, trade networks, and the like). Techniques of analysis may include graph theory, text analysis, multidimensional scaling and cluster analysis, and a variety of special models. Not limited to students in the major. Dist: QDS.  Lo.

QSS 54

Chasing the (Causal) Dragon: Intermediate Quantitative Data Analysis for Sociologists (Identical to SOCY 54)

20W: 10

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. SOCY 10 or equivalent and a basic understanding of STATA is required to enroll in this course. Dist: QDS. Houle.

QSS 81

Major Thesis Research

Fall: ARR

This course is the thesis track of the major and all students pursuing a major in QSS must submit a research project application no later than the Friday of the eighth week of the Spring term of a student’s third year. Students applying to write an honors thesis should have at time of application an overall GPA of 3.5 or higher.

QSS 82

Major One Quarter Project

Winter: ARR

This course is part of the two-track major in QSS. Students in the intensive project track of the QSS major must register for this course in the winter quarter of their fourth year on campus.

QSS 83

Minor One Quarter Project

Winter: ARR

All QSS minors must register for this course in the winter quarter of their fourth year on campus after fulfilling all minor requirements.