Jeff Gill

Essential Mathematics for Political and Social Research (eBook, PDF)

• Format: PDF

Produktbeschreibung

Essential Mathematics for Political and Social Research addresses an educational deficiency in the social and behavioral sciences. This 2006 book was the first of its kind to specifically address the comprehensive introduction to the mathematical principles needed by modern social scientists. The material introduces basic mathematical principles necessary to do analytical work in the social sciences, starting from first principles, but without unnecessary complexity. The core purpose is to present fundamental notions in standard notation and standard language with a clear, unified framework throughout. Through examples and exercises, this book is intended to not only motivate specific mathematical principles and practices, but also introduce the way that social science researchers use these tools. The intended emphasis is on conceptual understanding of key principles and their subsequent application.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 24. April 2006
• Englisch
• ISBN-13: 9781139855839
• Artikelnr.: 38449991

Autorenporträt

Jeff Gill is an associate professor of Political Science at the University of California, Davis. His current research is focused on projects such as Bayesian hierarchical models, MCMC theory, budgetary behavior in the House of Representatives, Congress, generalized linear model theory, and simulation techniques. He recently completed a book entitled Numerical Issues in Statistical Computing for the Social Scientist (with Altman and McDonald).

Inhaltsangabe

1. The basics
2. Analytic geometry
3. Linear algebra: vectors, matrices and operations
4. Linear algebra continued: matrix structure
5. Elementary scalar calculus
6. Additional topics in scalar and vector calculus
7. Probability theory
8. Random variables
9. Markov chains.