John Wilder Tukey's Books

The Collected Works of John W. Tukey

Philosophy and Principles of Data Analysis 1965-1986

By: L.V. Jones

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The Collected Works of John W. Tukey

Philosophy and Principles of Data Analysis 1965-1986

By: L.V. Jones

This volume of eleven articles compiles important papers by Tukey that examine the intriguing problems inherent in the area of multiple comparisons and provide a useful framework for thinking about them. Each volume in the set is indexed and contains a bibliography.

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Page Count

630

Publisher

CRC Press

Published Date

ISBN 10

0534051014

ISBN 13

9780534051013

The Practice of Data Analysis

Essays in Honor of John W. Tukey

By: John Wilder Tukey,David R. Brillinger,Luisa Turrin Fernholz,Stephan Morgenthaler

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The Practice of Data Analysis

Essays in Honor of John W. Tukey

By: John Wilder Tukey,David R. Brillinger,Luisa Turrin Fernholz,Stephan Morgenthaler

The essays in this collection discuss a wide array of recent developments in data analysis. They cover topics from "pure" data analysis, such as gaussianizing transformations and regression estimates, and from "applied" subjects such as estimating the abundance of birds in an area.

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Page Count

337

Publisher

Princeton University

Published Date

ISBN 10

0691057826

ISBN 13

9780691057828

Graphical Analysis of Multi-Response Data

By: Kaye Enid Basford,John Wilder Tukey

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Graphical Analysis of Multi-Response Data

By: Kaye Enid Basford,John Wilder Tukey

A comprehensive summary of new and existing approaches to analyzing multiresponse data, Graphical Analysis of Multiresponse Data emphasizes graphical procedures. These procedures are then used, in various ways, to analyze, summarize, and present data from a specific, well-known plant breeding trial. These procedures result in overlap plots, their corresponding semigraphical tables, scatter plot matrices, profiles across environments and attributes for individual genotypes and groups of genotypes, and principal components. The interpretation of these displays, as an aid to understanding, is illustrated and discussed. Techniques for choosing expressions for the observed quantities are also emphasized. Graphical Analysis of Multiresponse Data is arranged into three parts: What can usefully be done Consequences for the example Approaches and choices in more detail That structure enables the reader to obtain an overview of what can be found, and to then delve into various aspects more deeply if desired. Statisticians, data analysts, biometricians, plant breeders, behavioral scientists, social scientists, and engineering scientists will find Graphical Analysis of Multiresponse Data offers invaluable assistance. Its details are also of interest to scientists in private firms, government institutions, and research organizations who are concerned with the analysis and interpretation of experimental multiresponse data.

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Page Count

606

Publisher

CRC Press

Published Date

ISBN 10

1000715205

ISBN 13

9781000715200

An Introduction to Secondary Data Analysis with IBM SPSS Statistics

By: John MacInnes

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An Introduction to Secondary Data Analysis with IBM SPSS Statistics

By: John MacInnes

Many professional, high-quality surveys collect data on people′s behaviour, experiences, lifestyles and attitudes. The data they produce is more accessible than ever before. This book provides students with a comprehensive introduction to using this data, as well as transactional data and big data sources, in their own research projects. Here you will find all you need to know about locating, accessing, preparing and analysing secondary data, along with step-by-step instructions for using IBM SPSS Statistics. You will learn how to: Create a robust research question and design that suits secondary analysis Locate, access and explore data online Understand data documentation Check and ′clean′ secondary data Manage and analyse your data to produce meaningful results Replicate analyses of data in published articles and books Using case studies and video animations to illustrate each step of your research, this book provides you with the quantitative analysis skills you′ll need to pass your course, complete your research project and compete in the job market. Exercises throughout the book and on the book′s companion website give you an opportunity to practice, check your understanding and work hands on with real data as you′re learning.

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337

Publisher

SAGE

Published Date

ISBN 10

1473986958

ISBN 13

9781473986954

Regression

Linear Models in Statistics

By: N. H. Bingham,John M. Fry

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Regression

Linear Models in Statistics

By: N. H. Bingham,John M. Fry

Regression is the branch of Statistics in which a dependent variable of interest is modelled as a linear combination of one or more predictor variables, together with a random error. The subject is inherently two- or higher- dimensional, thus an understanding of Statistics in one dimension is essential. Regression: Linear Models in Statistics fills the gap between introductory statistical theory and more specialist sources of information. In doing so, it provides the reader with a number of worked examples, and exercises with full solutions. The book begins with simple linear regression (one predictor variable), and analysis of variance (ANOVA), and then further explores the area through inclusion of topics such as multiple linear regression (several predictor variables) and analysis of covariance (ANCOVA). The book concludes with special topics such as non-parametric regression and mixed models, time series, spatial processes and design of experiments. Aimed at 2nd and 3rd year undergraduates studying Statistics, Regression: Linear Models in Statistics requires a basic knowledge of (one-dimensional) Statistics, as well as Probability and standard Linear Algebra. Possible companions include John Haigh’s Probability Models, and T. S. Blyth & E.F. Robertsons’ Basic Linear Algebra and Further Linear Algebra.

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Page Count

293

Publisher

Springer Science & Business Media

Published Date

ISBN 10

1848829698

ISBN 13

9781848829695

Computing in Statistical Science through APL

By: Francis John Anscombe

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Computing in Statistical Science through APL

By: Francis John Anscombe

A t the terminal seated, the answering tone: pond and temple bell. ODAY as in the past, statistical method is profoundly affected by T resources for numerical calculation and visual display. The main line of development of statistical methodology during the first half of this century was conditioned by, and attuned to, the mechanical desk calculator. Now statisticians may use electronic computers of various kinds in various modes, and the character of statistical science has changed accordingly. Some, but not all, modes of modern computation have a flexibility and immediacy reminiscent of the desk calculator. They preserve the virtues of the desk calculator, while immensely exceeding its scope. Prominent among these is the computer language and conversational computing system known by the initials APL. This book is addressed to statisticians. Its first aim is to interest them in using APL in their work-for statistical analysis of data, for numerical support of theoretical studies, for simulation of random processes. In Part A the language is described and illustrated with short examples of statistical calculations. Part B, presenting some more extended examples of statistical analysis of data, has also the further aim of suggesting the interplay of computing and theory that must surely henceforth be typical of the develop ment of statistical science.

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Page Count

440

Publisher

Springer Science & Business Media

Published Date

ISBN 10

1461394503

ISBN 13

9781461394501

Mathematics as a Laboratory Tool

Dynamics, Delays and Noise

By: John Milton,Toru Ohira

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Mathematics as a Laboratory Tool

Dynamics, Delays and Noise

By: John Milton,Toru Ohira

The second edition of Mathematics as a Laboratory Tool reflects the growing impact that computational science is having on the career choices made by undergraduate science and engineering students. The focus is on dynamics and the effects of time delays and stochastic perturbations (“noise”) on the regulation provided by feedback control systems. The concepts are illustrated with applications to gene regulatory networks, motor control, neuroscience and population biology. The presentation in the first edition has been extended to include discussions of neuronal excitability and bursting, multistability, microchaos, Bayesian inference, second-order delay differential equations, and the semi-discretization method for the numerical integration of delay differential equations. Every effort has been made to ensure that the material is accessible to those with a background in calculus. The text provides advanced mathematical concepts such as the Laplace and Fourier integral transforms in the form of Tools. Bayesian inference is introduced using a number of detective-type scenarios including the Monty Hall problem.

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Page Count

650

Publisher

Springer Nature

Published Date

ISBN 10

3030695794

ISBN 13

9783030695798

Book's by John Wilder Tukey

The Collected Works of John W. Tukey

The Collected Works of John W. Tukey

The Practice of Data Analysis

The Practice of Data Analysis

Graphical Analysis of Multi-Response Data

Graphical Analysis of Multi-Response Data

An Introduction to Secondary Data Analysis with IBM SPSS Statistics

An Introduction to Secondary Data Analysis with IBM SPSS Statistics

Regression

Regression

Computing in Statistical Science through APL

Computing in Statistical Science through APL

Mathematics as a Laboratory Tool

Mathematics as a Laboratory Tool

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