Statistical Inference

According to Richard Shavelson, the goal of any good statistics book is for readers not only to learn the meaning of statistical concepts but also to be able to use these concepts to solve problems.

This book is suitable to be used as a text in introducing graduate courses or advanced undergraduate courses on the equilibrium statistical mechanics of bulk phases, interfaces, thin films and associ

This two-volume set aims to present as completely as possible the methods of statistical inference with special reference to their economic applications. The reader will find a description not only of the classical concepts and results of mathematical statistics, but also of concepts and methods recently developed for the specific needs of econometrics. The authors have sought to avoid an overly technical presentation and go to some lengths to encourage an intuitive understanding of the results by providing numerous examples throughout. The breadth of approaches and the extensive coverage of the two volumes provide for a thorough and entirely self-contained course in modern econometrics. Volume 1 provides an introduction to general concepts and methods in statistics and econometrics, and goes on to cover estimation and prediction. Volume 2 focuses on testing, confidence regions, model selection, and asymptotic theory.

This two-volume work aims to present as completely as possible the methods of statistical inference with special reference to their economic applications. The reader will find a description not only of the classical concepts and results of mathematical statistics, but also of concepts and methods recently developed for the specific needs of econometrics. The authors have sought to avoid an overly technical presentation and go to some lengths to encourage an intuitive understanding of the results by providing numerous examples throughout. The breadth of approaches and the extensive coverage of the two volumes provide for a thorough and entirely self-contained course in modern econometrics. Volume 1 provides an introduction to general concepts and methods in statistics and econometrics, and goes on to cover estimation and prediction. Volume 2 focuses on testing, confidence regions, model selection, and asymptotic theory.

This two-volume work aims to present as completely as possible the methods of statistical inference with special reference to their economic applications. The reader will find a description not only of the classical concepts and results of mathematical statistics, but also of concepts and methods recently developed for the specific needs of econometrics. The authors have sought to avoid an overly technical presentation and go to some lengths to encourage an intuitive understanding of the results by providing numerous examples throughout. The breadth of approaches and the extensive coverage of the two volumes provide for a thorough and entirely self-contained course in modern econometrics. Volume 1 provides an introduction to general concepts and methods in statistics and econometrics, and goes on to cover estimation and prediction. Volume 2 focuses on testing, confidence regions, model selection, and asymptotic theory.

Statistical mechanics is one of the crucial fundamental theories of physics, and in his new book Lawrence Sklar, one of the pre-eminent philosophers of physics, offers a comprehensive, non-technical introduction to that theory and to attempts to understand its foundational elements. Among the topics treated in detail are: probability and statistical explanation, the basic issues in both equilibrium and non-equilibrium statistical mechanics, the role of cosmology, the reduction of thermodynamics to statistical mechanics, and the alleged foundation of the very notion of time asymmetry in the entropic asymmetry of systems in time. The book emphasises the interaction of scientific and philosophical modes of reasoning, and in this way will interest all philosophers of science as well as those in physics and chemistry concerned with philosophical questions. The book could also be read by an informed general reader interested in the foundations of modern science.

The second edition of this very successful and authoritative set of tables still benefits from clear typesetting, which makes the figures easy to read and use. It has, however, been improved by the addition of new tables that provide Bayesian confidence limits for the binomial and Poisson distributions, and for the square of the multiple correlation coefficient, which have not been previously available. The intervals are the shortest possible, consistent with the requirement on probability. Great care has been taken to ensure that it is clear just what is being tabulated and how the values may be used; the tables are generally capable of easy interpolation. The book contains all the tables likely to be required for elementary statistical methods in the social, business and natural sciences. It will be an essential aid for teachers, researchers and students in those subjects where statistical analysis is not wholly carried out by computers.

This book presents both the fundamentals and the major research topics in statistical physics of systems out of equilibrium. It summarizes different approaches to describe such systems on the thermody

This text provides a firm grounding in the laws and principles of statistical mechanics and thermodynamics that are essential to the study of physics. It presents the subject in a remarkably fresh, cl

Sevenproblem-solving techniques include inference, classification of action sequences, subgoals, contradiction, working backward, relations between problems, andmathematical representatio

Experiment Design and Statistical Methods introduces the concepts, principles, and techniques for carrying out a practical research project either in real world settings or laboratories - relevant to

This book examines the consequences of misspecifications ranging from the fundamental to the nonexistent for the interpretation of likelihood-based methods of statistical estimation and interference. Professor White first explores the underlying motivation for maximum-likelihood estimation, treats the interpretation of the maximum-likelihood estimator (MLE) for misspecified probability models, and gives the conditions under which parameters of interest can be consistently estimated despite misspecification, and the consequences of misspecification, for hypothesis testing in estimating the asymptotic covariance matrix of the parameters. Although the theory presented in the book is motivated by econometric problems, its applicability is by no means restricted to economics. Subject to defined limitations, the theory applies to any scientific context in which statistical analysis is conducted using approximate models.

A collection of independent articles describes some mathematical problems recently developed in statistical physics and theoretical chemistry. The book introduces and reviews research on such topics

A detailed treatment on the use of statistical models representing physical phenomena. Considers the relevance of the popular normal distribution models and the applicability of exponential distributi

A unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms. Covers important approaches to obtaining an optima

This book of edited contributions provides a wide-ranging survey of the use of probability models for ranking data and it introduces new methods for the statistical analysis of ranking data. The contr

A graduate-level textbook, based on courses in statistical mechanics and field theory given by the author at the U. of Nice, France, and translated from the French edition of 1988. Includes a large nu

For both students of electrical engineering and practicing engineers, sets out statistical methods which can be used in the preparation, execution, evaluation, and interpretation of experiments of a r

Focusing on group sequential procedures, summarizes the sequential statistical methods used in anticancer, antiviral, cardiovascular, and gastrointestinal drug research and screening. The clinical and

Explores the heart of pattern recognition concepts, methods and applications using statistical, syntactic and neural approaches. Divided into four sections, it clearly demonstrates the similarities an

A textbook based on lectures delivered in Kyotoa, 1989. Martin argues that the Potts models, though a special class of statistical mechanical models, are, nonetheless, richly structured enough to illu

There are a number of important questions associated with statistical experiments: when does one given experiment yield more information than another; how can we measure the difference in information; how fast does information accumulate by repeating the experiment? The means of answering such questions has emerged from the work of Wald, Blackwell, LeCam and others and is based on the ideas of risk and deficiency. The present work which is devoted to the various methods of comparing statistical experiments, is essentially self-contained, requiring only some background in measure theory and functional analysis. Chapters introducing statistical experiments and the necessary convex analysis begin the book and are followed by others on game theory, decision theory and vector lattices. The notion of deficiency, which measures the difference in information between two experiments, is then introduced. The relation between it and other concepts, such as sufficiency, randomisation, distance, or

Written for the professional statistician or graduate statistics student, the primary objective of this book is to describe a system, based on the LISP language, for statistical computing and dynamic

This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering proble

Classic 1912 article reformulated the foundations of the statistical approach in mechanics. Largely still valid; essential reading for serious student. Covers older formulation of statistico-mechanica

The present set of notes grew out of our interest in the study of statistical transformation models, in particular exponential transfor- mation models. The latter class comprises as special cases all

This rigorous and practical account of the interpretation of mutagenicity test data draws upon the expertise of toxicologists and statisticians. Chemicals, such as drugs, food additives and pesticides, all need careful screening to eliminate potentially mutagenic compounds. Although guidelines exist on the performance of these tests, advice on data evaluation is scarce; this volume provides the statistical background necessary for toxicologists to understand, design and interpret mutagenicity tests. In addition to the nine chapters dealing with the different tests employed, there is an introductory chapter on some of the statistical principles involved, a glossary of useful terms and an appendix providing vital information on the availability of computer software. A large team of contributors and editors working under the auspices of the United Kingdom Environmental Mutagen Society (UKEMS) have contributed a wealth of first-hand experience in compiling this immensely practical book of

The Statistical Analysis of Discrete Data provides an up-to-date introduction to methods for analyzing discrete data. The text covers both single-sample problems and problems with structured means whi

This book is an expanded version of the Kahn's widely used text, An Introduction to Epidemiologic Methods (Oxford, 1983). It provides clear insight into the basic statistical tools used in epidemiolo

Professor Chandler and a colleague, David Wu, have prepared a solutions manual to Introduction to Modern Statistical Mechanics (Oxford 1987), to be used as an ancillary to the text. The instructive n

In these lectures we summarize certain results on models in statistical physics and quantum field theory and especially emphasize the deep relation- ship between these subjects. From a physical point

Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edi

Emphasizing the debt of science to nonspecialist intellectuals, Theodore Porter describes in detail the nineteenth-century background that produced the burst of modern statistical innovation of the ea

Leading physical chemist David Chandler takes a new approach to statistical mechanics to provide the only introductory-level work on the modern topics of renormalization group theory, Monte Carlo simu

Part I deals with principles of quantum statistical mechanics. Part II examines systems composed of independent molecules orother independent subsystems. Part III considers systems of interacti

A textbook for advanced undergraduate/first year graduate level courses in statistical methods in geography. Presents methods useful in research design, hypothesis testing, and analyzing spatial and f

This volume contains a selection of expository articles on quantum field theory and statistical mechanics by James Glimm and Arthur Jaffe. They include a solution of the original interacting quantum f

The main purpose of this book is to address the statistical issues for integrating independent studies. There exist a number of papers and books that discuss the mechanics of collecting, coding, and p

Introduction to basic statistical concepts and to concept of "adjustment" also covers solution by least squares of more complicated problems and takes into account the propagation of error, general pr

Practitioners of many skills face the need to make some realistic statement about the likely outcome of a future 'experiment of interest' on the basis of observed variability of outcomes in previously conducted related experiments. In this book the authors provide the predictor with the data and formulae which will assist in accurate forecasting, and suggest that an effective answer is to be found in the concept of predictive distribution within the framework of statistical prediction analysis. An applied mathematical approach is adopted throughout and the book is aimed at readers with some statistical knowledge, final year undergraduates, numerate scientists, technologists and medical workers interested in predictive techniques.