Understanding political methodology : a quantitative approach / Nathaniel L. Beck (professor of politics and public policy, NYU Wilf Family Department of Politics; associated professor of public service, NYU Wagner, USA).

Format:

Book

Author/Creator:

Beck, Nathaniel L., author.

Contributor:

Edward Elgar Publishing, publisher.

Series:

Understanding

Understanding series

Language:

English

Subjects (All):

Political science--Methodology.

Political science.

Genre:

Electronic books.

Physical Description:

1 online resource (176 pages)

Place of Publication:

Northampton : Edward Elgar Publishing, 2026.

Summary:

"This book presents an accessible overview of the key concepts underlying quantitative political methodology. Nathaniel L. Beck draws on existing quantitative analysis relating to political behavior and institutions to outline how and where these approaches are best used. Providing insights into the historical foundations and development of quantitative statistical analysis, Beck traces the evolution of probability, statistics, and political science through the 19th and early 20th centuries. He explores crucial themes and methods, covering measurement, neural nets, multiple regression, and maximum likelihood. Chapters shed light on data complications and other pivotal topics that are currently reshaping the field, including causality, networks, and the analysis of textual and visual data. Addressing real cases from the political science sphere, Beck investigates contemporary critiques of statistical hypothesis testing and proposes innovative ways of differentiating between models. Presenting a unique perspective on quantitative research methods, Understanding Political Methodology is a necessary resource for scholars and students of political science, sociology, public policy, and any social scientist using or teaching quantitative methods"-- Provided by publisher.

Contents:

Contents: Preface

1. Introduction

2. The prehistory of political methodology

3. The birth of political methodology

4. Multiple regression

5. Hypothesis testing applied to regression

6. Logit and maximum likelihood

7. A brief tour of various maximum likelihood-based estimators

8. Correcting for complicated errors

9. Time-series-cross-sectional data (and single time series)

10. Measurement

11. Causality: Experiments and near experiments

12. Causality without randomization: Controls

13. Networks

14. New data sources: Text and images

15. Conclusion: New data and new methods

Bibliography

Index.

Notes:

Description based on print record.

ISBN:

9781035336999 (e-book)

Access Restriction:

Restricted for use by site license.