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.

 

If you are graduating in 2024 or after please use this PDF iconMinor Worksheet

If you are graduating before 2024 you may use this PDF iconMinor Worksheet

 

 

 

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, GOV 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, QSS 36, or another course approved by the QSS Chair.

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 minor in quantitative social science includes QSS 17 and QSS 20. This requirement will be applied starting with the Class of 2024.

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 (GEOG 50), Geographical Information Systems
GEOG 54, Geovisualization
MATH 70, Elements of Multivariate Statistics and Statistical Learning
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 research seminar:  QSS 83