TY  - BOOK
AU  - Gailmard Sean
TI  - Statistical modeling and inference for social science
SN  - 9781107003149 (Hardback)
U1  - 001.891:519.22 
PY  - 2014///
CY  - New York
PB  - Cambridge University Press
KW  - Social sciences -Statistical methods
KW  - Descriptive statistics: data and information
KW  - Observable data and data-generating processes
KW  - Probability theory: basic properties of data-generating processes
KW  - Expectation and moments: summaries of data-generating processes
KW  - Probability and models: linking positive theories and data-generating processes
KW  - Sampling distributions: linking data-generating processes and observable data
KW  - Hypothesis testing: assessing claims about the data-generating process
KW  - stimation: recovering properties of the data-generating process
KW  - Causal inference: inferring causation from correlation
N2  - "This book provides an introduction to probability theory, statistical inference, and statistical modeling for social science researchers and Ph. D. students. Focusing on 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. Gailmard explains how social scientists express and test substantive theoretical arguments in various models. Chapter exercises require application of concepts to actual data and extend students' grasp of core theoretical concepts. Students will complete the book with the ability to read and critique statistical applications in their fields of interest"
ER  -