Minor

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.

Prerequisites

When you plan your course schedule, be aware that some of the prerequisites have their own prerequisites. Note as well that prerequisites can be double-counted across degree programs. For example, all majors in Economics, Government, and Sociology must take a "10"-level statistics course. Such a course will satisfy the "Introductory Statistics" prerequisite listed above.

Core Curriculum

The core curriculum for the major in quantitative social science includes QSS 17 and QSS 20.

Other Requirements

Beyond the prerequisites and the core curriculum listed above, the QSS minor requires three courses.

  • Two courses from the following:

COSC 74, Machine Learning and Statistical Data Analysis
GEOG 9.01, 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 19, Advanced Data Visualization
QSS 30, Special Topics in QSS
QSS 36, Mathematical Models in the Social Sciences
QSS 41, Analysis of Social Networks
QSS 45, Artificial Intelligence and Machine Learning for Social Science

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 two required courses listed above.

  • AND One quarter research project:  QSS 82