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Logic of Statistical Inference

Logic of Statistical Inference PDF Author: Ian Hacking
Publisher: Cambridge University Press
ISBN: 1316571769
Category : Philosophy
Languages : en
Pages : 229

Book Description
One of Ian Hacking's earliest publications, this book showcases his early ideas on the central concepts and questions surrounding statistical reasoning. He explores the basic principles of statistical reasoning and tests them, both at a philosophical level and in terms of their practical consequences for statisticians. Presented in a fresh twenty-first-century series livery, and including a specially commissioned preface written by Jan-Willem Romeijn, illuminating its enduring importance and relevance to philosophical enquiry, Hacking's influential and original work has been revived for a new generation of readers.

Logic of Statistical Inference

Logic of Statistical Inference PDF Author: Ian Hacking
Publisher: Cambridge University Press
ISBN: 1316571769
Category : Philosophy
Languages : en
Pages : 229

Book Description
One of Ian Hacking's earliest publications, this book showcases his early ideas on the central concepts and questions surrounding statistical reasoning. He explores the basic principles of statistical reasoning and tests them, both at a philosophical level and in terms of their practical consequences for statisticians. Presented in a fresh twenty-first-century series livery, and including a specially commissioned preface written by Jan-Willem Romeijn, illuminating its enduring importance and relevance to philosophical enquiry, Hacking's influential and original work has been revived for a new generation of readers.

Statistical Inference as Severe Testing

Statistical Inference as Severe Testing PDF Author: Deborah G. Mayo
Publisher: Cambridge University Press
ISBN: 1108563309
Category : Mathematics
Languages : en
Pages : 503

Book Description
Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.

The Logical Foundations of Statistical Inference

The Logical Foundations of Statistical Inference PDF Author: Henry E. Kyburg Jr.
Publisher: Springer Science & Business Media
ISBN: 9401021759
Category : Philosophy
Languages : en
Pages : 440

Book Description
Everyone knows it is easy to lie with statistics. It is important then to be able to tell a statistical lie from a valid statistical inference. It is a relatively widely accepted commonplace that our scientific knowledge is not certain and incorrigible, but merely probable, subject to refinement, modifi cation, and even overthrow. The rankest beginner at a gambling table understands that his decisions must be based on mathematical ex pectations - that is, on utilities weighted by probabilities. It is widely held that the same principles apply almost all the time in the game of life. If we turn to philosophers, or to mathematical statisticians, or to probability theorists for criteria of validity in statistical inference, for the general principles that distinguish well grounded from ill grounded generalizations and laws, or for the interpretation of that probability we must, like the gambler, take as our guide in life, we find disagreement, confusion, and frustration. We might be prepared to find disagreements on a philosophical and theoretical level (although we do not find them in the case of deductive logic) but we do not expect, and we may be surprised to find, that these theoretical disagreements lead to differences in the conclusions that are regarded as 'acceptable' in the practice of science and public affairs, and in the conduct of business.

Statistical Inference

Statistical Inference PDF Author: Michael W. Oakes
Publisher:
ISBN:
Category : Social Science
Languages : en
Pages : 204

Book Description


An Introduction to Probability and Inductive Logic

An Introduction to Probability and Inductive Logic PDF Author: Ian Hacking
Publisher: Cambridge University Press
ISBN: 9780521775014
Category : Mathematics
Languages : en
Pages : 326

Book Description
An introductory 2001 textbook on probability and induction written by a foremost philosopher of science.

The Theory of Gambling and Statistical Logic

The Theory of Gambling and Statistical Logic PDF Author: Richard A. Epstein
Publisher: Gulf Professional Publishing
ISBN: 9780122407611
Category : Business & Economics
Languages : en
Pages : 476

Book Description
Covering all aspects of gambling, The Theory of Gambling and Statistical Logic is mathematically sophisticated, but can be read for what it says about the games and strategies, skipping the technicalities. The material is fascinating and detailed, and the analysis is masterful.

Statistical Inference

Statistical Inference PDF Author: Helio S. Migon
Publisher: CRC Press
ISBN: 1439878803
Category : Mathematics
Languages : en
Pages : 388

Book Description
A Balanced Treatment of Bayesian and Frequentist Inference Statistical Inference: An Integrated Approach, Second Edition presents an account of the Bayesian and frequentist approaches to statistical inference. Now with an additional author, this second edition places a more balanced emphasis on both perspectives than the first edition. New to the Second Edition New material on empirical Bayes and penalized likelihoods and their impact on regression models Expanded material on hypothesis testing, method of moments, bias correction, and hierarchical models More examples and exercises More comparison between the approaches, including their similarities and differences Designed for advanced undergraduate and graduate courses, the text thoroughly covers statistical inference without delving too deep into technical details. It compares the Bayesian and frequentist schools of thought and explores procedures that lie on the border between the two. Many examples illustrate the methods and models, and exercises are included at the end of each chapter.

Basic Statistics in Criminology and Criminal Justice

Basic Statistics in Criminology and Criminal Justice PDF Author: David Weisburd
Publisher: Springer Nature
ISBN: 3030479676
Category : Social Science
Languages : en
Pages : 612

Book Description
This introductory textbook takes a building-block approach that emphasizes the application and interpretation of statistics in research in crime and justice. This text is meant for both students and professionals who want to gain a basic understanding of common statistical methods used in criminology and criminal justice before advancing to more complex statistical analyses in future volumes. This book emphasizes comprehension and interpretation. As the statistical methods discussed become more complex and demanding to compute, it integrates statistical software. It provides readers with an accessible understanding of popular statistical programs used to examine real-life crime and justice problems (including SPSS, Stata, and R). In addition, the book includes supplemental resources such as a glossary of key terms, practice questions, and sample data. Basic Statistics in Criminology and Criminal Justice aims to give students and researchers a core understanding of statistical concepts and methods that will leave them with the confidence and tools to tackle the statistical problems in their own research work.

Statistical Inference for Everyone

Statistical Inference for Everyone PDF Author: Brian Blais
Publisher: Createspace Independent Publishing Platform
ISBN: 9781499715071
Category : Mathematics
Languages : en
Pages : 200

Book Description
Approaching an introductory statistical inference textbook in a novel way, this book is motivated by the perspective of "probability theory as logic". Targeted to the typical "Statistics 101" college student this book covers the topics typically treated in such a course - but from a fresh angle. This book walks through a simple introduction to probability, and then applies those principles to all problems of inference. Topics include hypothesis testing, data visualization, parameter inference, and model comparison. Statistical Inference for Everyone is freely available under the Creative Commons License, and includes a software library in Python for making calculations and visualizations straightforward.

Principles of Statistical Inference

Principles of Statistical Inference PDF Author: D. R. Cox
Publisher: Cambridge University Press
ISBN: 1139459139
Category : Mathematics
Languages : en
Pages : 227

Book Description
In this definitive book, D. R. Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more personal assessment of the merits of different ideas. The content ranges from the traditional to the contemporary. While specific applications are not treated, the book is strongly motivated by applications across the sciences and associated technologies. The mathematics is kept as elementary as feasible, though previous knowledge of statistics is assumed. The book will be valued by every user or student of statistics who is serious about understanding the uncertainty inherent in conclusions from statistical analyses.