A Mathematics Course for Political and Social Research

by Will H. Moore, David A. Siegel

Political science and sociology increasingly rely on mathematical modeling and sophisticated data analysis, and many graduate programs in these fields now require students to take a "math camp" or a semester-long or yearlong course to acquire the necessary skills. Available textbooks are written for mathematics or economics majors, and fail to convey to students of political science and sociology the reasons for learning often-abstract mathematical concepts. A Mathematics Course for Political and Social Research fills this gap, providing both a primer for math novices in the social sciences and a handy reference for seasoned researchers.


The book begins with the fundamental building blocks of mathematics and basic algebra, then goes on to cover essential subjects such as calculus in one and more than one variable, including optimization, constrained optimization, and implicit functions; linear algebra, including Markov chains and eigenvectors; and probability. It describes the intermediate steps most other textbooks leave out, features numerous exercises throughout, and grounds all concepts by illustrating their use and importance in political science and sociology.

Genres: Mathematics, Politics, Sociology, Reference

450 pages, Paperback

First published January 1, 2013

Reviews

[David Goh · Rating 4 out of 5]

Informative and full of good tricks. However, the style of writing is occasionally a tad too conversational, and I lose the line of argument.

I recommend watching 3 Blue 1 Brown's videos on linear algebra before going into the relevant sections here. While this book effectively zooms in on the use of Mathematics in social science research, the fundamental intuitions gained from 3B1B's purely mathematical perspective help to ease one into the realm of vectors and matrices, especially if this is the first time you're encountering these topics.

Multivariable Calculus and Optimisation, the final section, also hit me like a sledgehammer compared to the earlier sections of the book. Probably not the only resource one should use to study Optimisation from scratch.

[Nick Geiser · Rating 4 out of 5]

Excellent textbook written for a specific niche audience: social science (esp. political science) grad students with "math phobia" who need to brush up on their math skills to pass their first-year classes and learn enough to read papers in their discipline. The focus is on intuition and practical applications rather than on formal rigor. As the authors say in the preface, this is not a formal text in mathematics. I found it helpful and I appreciate the approach they took instead.

[Iliya Liampert · Rating 4 out of 5]

Required textbook for grad summer math class.

A great introduction to many core mathematical and statistical concepts that are permeating political science. It helped me to "catch up" as well as learn new concepts that I had never seen before.

The only downside is that occasionally, the writing becomes loaded with examples that are mixed together with newly introduced material. It is nevertheless a difficult task to write a good book on this topic, which I think the authors managed to complete successfully.

[J.R. · Rating 3 out of 5]

Helpful in understanding the logic of the equations used in statistical modeling. It's a great supplement for those who, like myself, need a better grasp of the math before applying statistics in software.