Quantitative Social Science

M. C. Herron (QSS), Y. Horiuchi (Government), S. D. Pauls (Mathematics), D. Rockmore (Mathematics, Computer Science), A. A. Samwick (Economics), R. A. Shumsky (Operations at Tuck Business School); Adjunct Assistant Professor J. Chipman (Geography and Earth Sciences), Erika Moen (Biomedical Data Science), Jaren Haber (Postdoc). 

The Program in Quantitative Social Science (QSS) brings together Dartmouth faculty and students who are interested in applying statistical, computational, and mathematical tools to social science questions. QSS offers undergraduates a minor and a major, both of which combine quantitative training with one or more of the social sciences. Through QSS, Dartmouth undergraduates can integrate the power of modern quantitative and computational methods with the substance of a social science discipline.

The Major in Quantitative Social Science

The major consists of courses to be selected from the following areas:

• Programming: either COSC 1 or ENGS 20, or another programming course approved by the QSS Chair.
• Mathematics: MATH 3 and MATH 8.
• Introductory statistics: either ECON 10, GOVT 10, MATH 10, QSS 15, PSYC 10, or SOCY 10, or another introductory statistics course approved by the QSS Chair.
• Intermediate statistics: either ECON 20, GOV 19.01, MATH 40, MATH 50, or QSS 54 or another intermediate statistics course approved by the QSS Chair.
• Mathematical Modeling: either ECON 21 or QSS 18, QSS 30.04 or another game theory course approved by the QSS Chair.
• Introductory social science: one of ANTH 1, ANTH 6, ECON 1, EDUC 1, GEOG 1, GEOG 6, GOV 3, GOV 4, GOV 5, GOV 6, PSYC 1, or SOC 1, or another course approved by the QSS Chair.
• QSS 20: COSC 1, ENGS 20, or another programming course approved by the QSS Chair.
• QSS 30.04: MATH 20.

Core Curriculum:

The core curriculum for the major in Quantitative Social Science includes QSS 17 and QSS 20. This requirement will be applied starting with the Class of 2024.

Methods-oriented requirements:

MATH 11, MATH 13, or MATH 22.

AND two courses from the following:

COSC 74, Machine Learning and Statistical Data Analysis
GEOG 50, Geographical Information Systems
GEOG 54, Geovisualization
MATH 50, Introduction to Linear Models
MATH 76, Topics in Applied Mathematics (to be approved by the QSS Chair)
QSS 17, Data Visualization
QSS 30, Special Topics in QSS
QSS 36, Mathematical Models in the Social Sciences
QSS 41, Analysis of Social Networks

The special topics course, QSS 30, may be taken more than once as long as different electives are selected.  Moreover, with permission of the QSS Chair students may substitute other courses offered at Dartmouth for any of the two required courses listed above.

Social science requirements:

Four non-introductory courses that focus on a social science area of the student's choosing.  A student pursuing the major in QSS should consider the extent to which his or her social science courses are coherent, and the QSS Chair will be available to offer guidance on this.

To graduate with a major in QSS, a student must complete an independent research project. At the end of his or her third year on campus, each QSS major must choose one of two project options: either an intensive, one quarter project or a three quarters honors thesis. The honors thesis option requires approval from the program, and QSS honors theses are governed by guidelines established by the College. Per these guidelines, a student completing a thesis judged to be of sufficiently high quality will graduate from Dartmouth with Honors or with High Honors in QSS. A QSS major who elects the intensive project track will work on his or her project during the winter term of the student's fourth year on campus. Any exceptions to this rule must be approved by the QSS Director of Undergraduate Research (DUR) and the QSS Chair. Participating in the thesis track requires work and engagement during the fall, winter, and spring terms of a student’s fourth year. Students applying to write an honors thesis in QSS should have at time of application an overall grade point average of 3.5 or higher. In limited and extraordinary circumstances, a student pursuing a major in QSS will be permitted to change tracks after the start of his or her fourth year. The QSS Chair and DUR are responsible for assessing and, if necessary approving, any such proposed moves. A student completing an intensive, one quarter research project will take QSS 82 the student’s last year on campus. A student in the honors thesis track of the QSS major will take QSS 81 in the winter. For further details on application and timing for the two research project tracks, consult the QSS Chair.

The QSS minor was designed based on the belief that quantitatively- and computationally-oriented students who have interests in social science should be taught a core set of skills. Such students need to know the basics of computer programming; they need a foundation in calculus; they need to know the basics of statistical inference; they need exposure to mathematical modeling; they need to be familiar with research design; and, they need hands-on exposure to the rewards and difficulties of research.   The QSS minor embodies these objectives and empowers students to answer important empirical questions about the world.

The minor consists of courses to be selected from the following areas:

Five prerequisites: 

• Programming: either COSC 1 or ENGS 20, or another programming course approved by the QSS Chair.

• Mathematics: MATH 8.

• Introductory statistics: either ECON 10, ENVS 10, GOVT 10, MATH 10, QSS 15, PSYC 10, or SOCY 10, or another introductory statistics course approved by the QSS Chair.

• Intermediate statistics: either ECON 20, GOV 19.01, MATH 40, MATH 50, QSS 54, or another intermediate statistics course approved by the QSS Chair.

• Mathematical modeling: either ECON 21, QSS 18, QSS 30.04, or QSS 36, or another course approved by the QSS Chair.

• QSS 20: COSC 1 or ENGS 20, or another programming course approved by the QSS Chair.

• QSS 30.04: MATH 20.

Core Curriculum:

The core curriculum for the minor in Quantitative Social Science includes QSS 17 and QSS 20. This requirement will be applied starting with the Class of 2024.

AND Three courses from the following:

COSC 74, Machine Learning and Statistical Data Analysis
GEOG 50, Geographical Information Systems
GEOG 54, Geovisualization
MATH 70, Elements of Multivariate Statistics and Statistical Learning
QSS 17, Data Visualization
QSS 30, Special Topics in QSS
QSS 41, Analysis of Social Networks

The special topics course, QSS 30, may be taken more than once.  Moreover, with permission of the QSS chair students may substitute other courses offered at Dartmouth for any of the three required courses listed above.

AND One quarter research project:  QSS 82