Statistical Modeling and Inference for Social Science

by Sean Gailmard

Series: Analytical Methods for Social Research

Subject categories
ISBNs
  • 9781107003149
  • 9781139989442
  • 9781139984829
Written specifically for graduate students and practitioners beginning social science research, Statistical Modeling and Inference for Social Science covers the essential statistical tools, models and theories that make up the social scientist's toolkit. Assuming no prior knowledge of statistics, this textbook introduces students to probability theory, statistical inference and statistical modeling, and emphasizes the connection between statistical procedures and social science theory. Sean Gailmard develops core statistical theory as a set of tools to model and assess relationships between variables - the primary aim of social scientists - and demonstrates the ways in which social scientists express and test substantive theoretical arguments in various models. Chapter exercises guide students in applying concepts to data, extending their grasp of core theoretical concepts. Students will also gain the ability to create, read and critique statistical applications in their fields of interest.

Subject categories
ISBNs
  • 9781107003149
  • 9781139989442
  • 9781139984829

In The Press

'With careful consideration for both rigor and intuition, Gailmard fills a large void in the social science literature. Those seeking clear mathematical exposition will not be disappointed. Those hoping for substantive applications to illuminate the data analysis will also be pleased. This book strikes a nearly perfect balance.' Wendy K. Tam Cho, National Center for Supercomputing Applications and University of Illinois, Urbana-Champaign

Subject categories
ISBNs
  • 9781107003149
  • 9781139989442
  • 9781139984829