Foundations of Agnostic Statistics - Peter M. Aronow, Benjamin T. Miller

Foundations of Agnostic Statistics

Buch | Hardcover
314 Seiten
2019
Cambridge University Press (Verlag)
978-1-107-17891-5 (ISBN)
109,70 inkl. MwSt
This book provides a rigorous but accessible treatment of modern statistical methodology for researchers in the social and health sciences. It provides readers with the mathematical tools to critically engage with cutting-edge statistical methods.
Reflecting a sea change in how empirical research has been conducted over the past three decades, Foundations of Agnostic Statistics presents an innovative treatment of modern statistical theory for the social and health sciences. This book develops the fundamentals of what the authors call agnostic statistics, which considers what can be learned about the world without assuming that there exists a simple generative model that can be known to be true. Aronow and Miller provide the foundations for statistical inference for researchers unwilling to make assumptions beyond what they or their audience would find credible. Building from first principles, the book covers topics including estimation theory, regression, maximum likelihood, missing data, and causal inference. Using these principles, readers will be able to formally articulate their targets of inquiry, distinguish substantive assumptions from statistical assumptions, and ultimately engage in cutting-edge quantitative empirical research that contributes to human knowledge.

Peter M. Aronow is an Associate Professor of Political Science, Public Health (Biostatistics), and Statistics and Data Science at Yale University, Connecticut and is affiliated with the University's Institution for Social and Policy Studies, Center for the Study of American Politics, Institute for Network Science, and Operations Research Doctoral Program. Benjamin T. Miller is a doctoral candidate in Political Science at Yale University, Connecticut. In 2012, Mr Miller received a B.A. in Economics and Mathematics from Amherst College.

Introduction; Part I. Probability: 1. Probability theory; 2. Summarizing distributions; Part II. Statistics: 3. Learning from random samples; 4. Regression; 5. Parametric models; Part III. Identification: 6. Missing data; 7. Causal inference.

Erscheinungsdatum
Zusatzinfo Worked examples or Exercises; 35 Line drawings, black and white
Verlagsort Cambridge
Sprache englisch
Maße 156 x 235 mm
Gewicht 650 g
Themenwelt Mathematik / Informatik Mathematik Statistik
Studium 1. Studienabschnitt (Vorklinik) Med. Psychologie / Soziologie
Studium Querschnittsbereiche Epidemiologie / Med. Biometrie
Sozialwissenschaften Soziologie Empirische Sozialforschung
ISBN-10 1-107-17891-6 / 1107178916
ISBN-13 978-1-107-17891-5 / 9781107178915
Zustand Neuware
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