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Statistical Modeling and Inference for Social Science (Analytical Methods for Social Research) by [Sean Gailmard]

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Sean Gailmard

Statistical Modeling and Inference for Social Science (Analytical Methods for Social Research) Kindle Edition

by Sean Gailmard (Author) Format: Kindle Edition

4.4 14 ratings

Part of: Analytical Methods for Social Research (15 books)

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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.

ISBN-10

9781139982504
ISBN-13

978-1107003149
Sticky notes

On Kindle Scribe
Publisher

Cambridge University Press
Publication date

June 9 2014
Part of series

Analytical Methods for Social Research
Language

English
File size

11602 KB
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Product description

Review

"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

"This is the single best book on modeling in social science - it goes beyond any extant book and will without a doubt become the standard text in methods courses throughout the social sciences."
James N. Druckman, Payson S. Wild Professor of Political Science, Northwestern University, Illinois

"In Statistical Modeling and Inference for Social Science, Gailmard provides a complete and well-written review of statistical modeling from the modern perspective of causal inference. It provides all the material necessary for an introduction to quantitative methods for social science students."
Jonathan N. Katz, Kay Sugahara Professor of Social Sciences and Statistics, and Chair, Division of the Humanities and Social Sciences, California Institute of Technology --This text refers to the paperback edition.

Book Description

This textbook is an introduction to probability theory, statistical inference and statistical modeling for graduate students and practitioners beginning social science research. --This text refers to the paperback edition.

Product details

ASIN ‏ : ‎ B00JXII890
Publisher ‏ : ‎ Cambridge University Press (June 9 2014)
Language ‏ : ‎ English
File size ‏ : ‎ 11602 KB
Simultaneous device usage ‏ : ‎ Up to 4 simultaneous devices, per publisher limits
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Enabled
Sticky notes ‏ : ‎ On Kindle Scribe
Print length ‏ : ‎ 393 pages

Best Sellers Rank: #1,227,236 in Kindle Store (See Top 100 in Kindle Store)
- #509 in Econometrics in Finance
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- #557 in Probability & Statistics (Kindle Store)

Customer Reviews:
4.4 14 ratings

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Sean Gailmard

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Customer reviews

4.4 out of 5

14 global ratings

5 star		69%
4 star		9%
3 star		13%
2 star		9%
1 star 0% (0%)		0%

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Top review from Canada

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PS

Two Stars

Reviewed in Canada 🇨🇦 on January 13, 2015

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Really not a good book.

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Justin Gross

Great for a one-semester intro course for PhD political science or sociology

Reviewed in the United States 🇺🇸 on August 8, 2016

Verified Purchase

This is the best book currently available for a single semester statistical methods course for PhD social scientists. It covers a lot of ground at an appropriate level of sophistication and in an unconventional order that is particularly well suited to the applied researcher who wants to know "what's the point of this?"

6 people found this helpful

Daitoryu

only good if you know 0 math/stat

Reviewed in the United States 🇺🇸 on February 13, 2017

Verified Purchase

First let me make this clear: the quality of a book should really be defined w.r.t a reader's rather individual needs; a book perfect for one person may just be useless for another.
I gave this book a 3 star because, it is only good if you have next to zero prior knowledge of mathematics (especially calculus) and statistics. I picked up this book as a refresher because I've taken mathematical statistics before, and I found this book overly "wordy" to the extent it gets a bit confusing sometimes. Some concepts could have been demonstrated much cleaner and simpler using math plus some examples. So, if you are in a similar position (looking for refresher on math stat) I highly recommend "mathematical statistics with applications" by Wackerly instead: it has more math (but you will be perfectly fine as long as you know calculus) and far fewer words (so you can read through things quickly), but the exposition is crystal clear with many good examples to fix ideas.

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Follow the Author

Statistical Modeling and Inference for Social Science (Analytical Methods for Social Research) Kindle Edition

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Book Description

About the Author

Product details

About the author

Sean Gailmard

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