Mathematics for Social Scientists

Glauco Peres da Silva, University of São Paulo 


This course is designed for students who seek to acquire basic training in mathematics applied to quantitative analysis in the social sciences. It is directed toward students with limited training in mathematics. This course will present basic concepts commonly used in political science research, such as mathematical notation, basic set theory, various number systems, the algebra of numbers, the notion of a function, several important classes of functions, and solutions to systems of linear equations. The course will also provide an introduction to differential and integral calculus and applied matrix algebra. To complement lectures, students will apply the concepts taught in lectures to analyze problems using the mathematical and software packages commonly used in quantitative social science research.

For those of you considering enrolling in this course, watch the video below to find out more!


This course runs January 21-25,2019.


This course will present fundamental mathematics principles focusing on students with limited backgrounds in mathematics. This course will adopt a hands-on approach in which morning lectures will be followed by afternoon laboratory sessions in which student will apply the concepts taught in the morning to solve problems. Classes will be divided in three steps: a) lectures; b) in-class exercises; c) applications based on social science research.

Teaching Fellow: Mauricio Izumi, University of São Paulo


1.    Preliminaries

2.    Functions and limits

3.    Derivatives and Integrals

4.    Linear Algebra

5.    Optimization

6.    Maxima and Minima Global and Local

7.    Lagrange Multiplier

Required Readings

Gill, Jeff. 2006. Essential Mathematics for Political and Social Research. 1st Edition, Cambridge University Press.

Moore, Will, and David Siegel. 2013. A Mathematics Course for Political & Social Research. 1st edition, Princeton, N.J.: Princeton University Press.

Simon, Carl, and Lawrence Blume. 1994. Mathematics for Economists. 1st edition, W. W. Norton & Co. 


A background in algebra is helpful.