Probability Theory and Statistical Inference: Empirical Modeling with Observational Data

Spanos, Aris

ISBN 10: 1316636372 / ISBN 13: 9781316636374

Edité par Cambridge University Press, 2019

A propos de cet article

N° de réf. du vendeur I-9781316636374

Détails bibliographiques

• Titre: Probability Theory and Statistical Inference: Empirical Modeling with Observational Data
• Éditeur: Cambridge University Press
• Date de parution: 2019
• Langue: anglais
• ISBN à 10 chiffres: 1316636372
• ISBN à 13 chiffres: 9781316636374
• Reliure: Couverture souple
• Édition: 2ème Édition
• État de l'article: New

A propos de ce titre

Synopsis

Doubt over the trustworthiness of published empirical results is not unwarranted and is often a result of statistical mis-specification: invalid probabilistic assumptions imposed on data. Now in its second edition, this bestselling textbook offers a comprehensive course in empirical research methods, teaching the probabilistic and statistical foundations that enable the specification and validation of statistical models, providing the basis for an informed implementation of statistical procedure to secure the trustworthiness of evidence. Each chapter has been thoroughly updated, accounting for developments in the field and the author's own research. The comprehensive scope of the textbook has been expanded by the addition of a new chapter on the Linear Regression and related statistical models. This new edition is now more accessible to students of disciplines beyond economics and includes more pedagogical features, with an increased number of examples as well as review questions and exercises at the end of each chapter.

À propos de l?auteur

Aris Spanos is Wilson E. Schmidt Professor of Economics at Virginia Polytechnic Institute and State University. He is the author of Statistical Foundations of Econometric Modelling (Cambridge, 1986) and, with D. G. Mayo, Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science (Cambridge, 2010).