More Books:

Essential Mathematics for Political and Social Research
Language: en
Pages: 448
Authors: Jeff Gill
Categories: Mathematics
Type: BOOK - Published: 2006-04-24 - Publisher: Cambridge University Press

This 2006 book addresses the comprehensive introduction to the mathematical principles needed by modern social scientists.
Statistical Modeling and Inference for Social Science
Language: en
Pages: 388
Authors: Sean Gailmard
Categories: Business & Economics
Type: BOOK - Published: 2014-06-09 - Publisher: Cambridge University Press

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
Spatial Analysis for the Social Sciences
Language: en
Pages: 258
Authors: David Darmofal
Categories: Political Science
Type: BOOK - Published: 2015-10-31 - Publisher: Cambridge University Press

This book shows how to model the spatial interactions between actors that are at the heart of the social sciences.
Time Series Analysis for the Social Sciences
Language: en
Pages:
Authors: Janet M. Box-Steffensmeier, John R. Freeman, Matthew P. Hitt, Jon C. W. Pevehouse
Categories: Political Science
Type: BOOK - Published: 2014-12-22 - Publisher: Cambridge University Press

Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples
Maximum Likelihood for Social Science
Language: en
Pages:
Authors: Michael D. Ward, John S. Ahlquist
Categories: Political Science
Type: BOOK - Published: 2018-12-31 - Publisher: Cambridge University Press

This volume provides a practical introduction to the method of maximum likelihood as used in social science research. Ward and Ahlquist focus on applied computation in R and use real social science data from actual, published research. Unique among books at this level, it develops simulation-based tools for model evaluation