## New Cambridge Statistical Tables

**Author**: Dennis V. Lindley,William F. Scott

**Publisher:**Cambridge University Press

**ISBN:**9780521484855

**Category:**Mathematics

**Page:**96

**View:**328

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The latest edition of this very successful and authoritative set of tables, first published in 1984, still benefits from clear typesetting, which makes the figures easy to read and use, but has been improved by the addition of new tables. These give 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. The authors have taken great care to ensure the clarity of the tables and how their values may be used; the tables are easily interpolated. The book contains all the tables likely to be required for elementary statistical methods in the social, business and natural sciences, and will be an essential aid for teachers, users and students in these areas.

## Statistics on the Table

*The History of Statistical Concepts and Methods*

**Author**: Stephen M. Stigler

**Publisher:**Harvard University Press

**ISBN:**9780674009790

**Category:**Mathematics

**Page:**488

**View:**3970

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This lively collection of essays examines statistical ideas with an ironic eye for their essence and what their history can tell us for current disputes. The topics range from seventeenth-century medicine and the circulation of blood, to the cause of the Great Depression and the effect of the California gold discoveries of 1848 upon price levels, to the determinations of the shape of the Earth and the speed of light, to the meter of Virgil's poetry and the prediction of the Second Coming of Christ.

## Mathematics for Economics and Finance

*Methods and Modelling*

**Author**: Martin Anthony,Norman Biggs

**Publisher:**Cambridge University Press

**ISBN:**1139643266

**Category:**Mathematics

**Page:**N.A

**View:**5908

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Mathematics has become indispensable in the modelling of economics, finance, business and management. Without expecting any particular background of the reader, this book covers the following mathematical topics, with frequent reference to applications in economics and finance: functions, graphs and equations, recurrences (difference equations), differentiation, exponentials and logarithms, optimisation, partial differentiation, optimisation in several variables, vectors and matrices, linear equations, Lagrange multipliers, integration, first-order and second-order differential equations. The stress is on the relation of maths to economics, and this is illustrated with copious examples and exercises to foster depth of understanding. Each chapter has three parts: the main text, a section of further worked examples and a summary of the chapter together with a selection of problems for the reader to attempt. For students of economics, mathematics, or both, this book provides an introduction to mathematical methods in economics and finance that will be welcomed for its clarity and breadth.

## Statistics for Anthropology

**Author**: Lorena Madrigal

**Publisher:**Cambridge University Press

**ISBN:**1107375509

**Category:**Science

**Page:**N.A

**View:**3338

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Anthropology as a discipline is rapidly becoming more quantitative, and anthropology students are now required to develop sophisticated statistical skills. This book provides students of anthropology with a clear, step-by-step guide to univariate statistical methods, demystifying the aspects that are often seen as difficult or impenetrable. Explaining the central role of statistical methods in anthropology and using only anthropological examples, the book provides a solid footing in statistical techniques. Beginning with basic descriptive statistics, this new edition also covers more advanced methods such as analyses of frequencies and variance, simple and multiple regression analysis with dummy and continuous variables. It addresses commonly encountered problems such as small samples and non-normality. Each statistical technique is accompanied by clearly worked examples and the chapters end with practice problem sets. Many of the datasets are available for download at www.cambridge.org/9780521147088.

## Bootstrap Methods and Their Application

**Author**: A. C. Davison,D. V. Hinkley

**Publisher:**Cambridge University Press

**ISBN:**9780521574716

**Category:**Computers

**Page:**582

**View:**3448

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This book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. Included with the book is a disk of purpose-written S-Plus programs for implementing the methods described in the text. Computer algorithms are clearly described, and computer code is included on a 3-inch, 1.4M disk for use with IBM computers and compatible machines. Users must have the S-Plus computer application. Author resource page: http://statwww.epfl.ch/davison/BMA/

## Statistical Modeling and Inference for Social Science

**Author**: Sean Gailmard

**Publisher:**Cambridge University Press

**ISBN:**1107003148

**Category:**Business & Economics

**Page:**388

**View:**9299

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Written specifically for graduate students and practitioners beginning social science research, Statistical Modeling and Inference for Social Science covers the essential statistical tools, models and theories that make up the social scientist's toolkit. Assuming no prior knowledge of statistics, this textbook introduces students to probability theory, statistical inference and statistical modeling, and emphasizes the connection between statistical procedures and social science theory. Sean Gailmard develops core statistical theory as a set of tools to model and assess relationships between variables - the primary aim of social scientists - and demonstrates the ways in which social scientists express and test substantive theoretical arguments in various models. Chapter exercises guide students in applying concepts to data, extending their grasp of core theoretical concepts. Students gain the ability to create, read and critique statistical applications in their fields of interest.

## Computer Age Statistical Inference

*Algorithms, Evidence, and Data Science*

**Author**: Bradley Efron,Trevor Hastie

**Publisher:**Cambridge University Press

**ISBN:**1108107958

**Category:**Mathematics

**Page:**N.A

**View:**8197

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The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

## Practical Statistics for Astronomers

**Author**: J. V. Wall,C. R. Jenkins

**Publisher:**Cambridge University Press

**ISBN:**9780521456166

**Category:**Mathematics

**Page:**277

**View:**7093

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Presents the most relevant statistical and probabilistic machinery for use in observational astronomy.

## 100 Statistical Tests

**Author**: Gopal K Kanji

**Publisher:**SAGE

**ISBN:**9781412923767

**Category:**Mathematics

**Page:**242

**View:**7108

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This expanded and updated Third Edition of Gopal K. Kanji’s best-selling resource on statistical tests covers all the most commonly used tests with information on how to calculate and interpret results with simple datasets. Each entry begins with a short summary statement about the test’s purpose, and contains details of the test objective, the limitations (or assumptions) involved, a brief outline of the method, a worked example, and the numerical calculation. 100 Statistical Tests, Third Edition is the one indispensable guide for users of statistical materials and consumers of statistical information at all levels and across all disciplines.

## Tables of the Ordinates and Probability Integral of the Distribution of the Correlation Coefficient in Small Samples

**Author**: F. N. David

**Publisher:**Cambridge University Press

**ISBN:**9780521124126

**Category:**Mathematics

**Page:**112

**View:**813

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The theory of correlation finds its origins in the pioneering work of Francis Galton. Lark Pearson and R. A. Fisher did much to develop the foundations of the subject in the early part of the twentieth century as the theory of mathematical statistics and its applications took shape. This book dates back to the 1930s, meeting the requirements of the time by providing tables of correlation coefficients to a considerable degree of accuracy, whilst also discussing a number of illustrative examples that employ the tables to provide a guide in drawing inference from observation.

## The R Book

**Author**: Michael J. Crawley

**Publisher:**John Wiley & Sons

**ISBN:**1118448960

**Category:**Mathematics

**Page:**1080

**View:**6092

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Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition: ‘…if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008) ‘The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book…’ (Professional Pensions, July 2007)

## Intermediate Statistics and Econometrics

*A Comparative Approach*

**Author**: Dale J. Poirier

**Publisher:**MIT Press

**ISBN:**9780262161497

**Category:**Business & Economics

**Page:**715

**View:**7822

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The standard introductory texts to mathematical statistics leave the Bayesian approach to be taught later in advanced topics courses—giving students the impression that Bayesian statistics provide but a few techniques appropriate in only special circumstances. Nothing could be further from the truth, argues Dale Poirier, who has developed a course for teaching comparatively both the classical and the Bayesian approaches to econometrics. Poirier's text provides a thoroughly modern, self-contained, comprehensive, and accessible treatment of the probability and statistical foundations of econometrics with special emphasis on the linear regression model. Written primarily for advanced undergraduate and graduate students who are pursuing research careers in economics, Intermediate Statistics and Econometrics offers a broad perspective, bringing together a great deal of diverse material. Its comparative approach, emphasis on regression and prediction, and numerous exercises and references provide a solid foundation for subsequent courses in econometrics and will prove a valuable resource to many nonspecialists who want to update their quantitative skills. The introduction closes with an example of a real-world data set—the Challenger space shuttle disaster—that motivates much of the text's theoretical discussion. The ten chapters that follow cover basic concepts, special distributions, distributions of functions of random variables, sampling theory, estimation, hypothesis testing, prediction, and the linear regression model. Appendixes contain a review of matrix algebra, computation, and statistical tables.

## Statistical Methods For Research Workers

**Author**: R.A. Fisher

**Publisher:**Genesis Publishing Pvt Ltd

**ISBN:**9788130701332

**Category:**Biometry

**Page:**354

**View:**4314

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## Statistical Methods in the Atmospheric Sciences

**Author**: Daniel S. Wilks

**Publisher:**Academic Press

**ISBN:**0123850231

**Category:**Science

**Page:**704

**View:**7671

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Statistical Methods in the Atmospheric Sciences, Third Edition, explains the latest statistical methods used to describe, analyze, test, and forecast atmospheric data. This revised and expanded text is intended to help students understand and communicate what their data sets have to say, or to make sense of the scientific literature in meteorology, climatology, and related disciplines. In this new edition, what was a single chapter on multivariate statistics has been expanded to a full six chapters on this important topic. Other chapters have also been revised and cover exploratory data analysis, probability distributions, hypothesis testing, statistical weather forecasting, forecast verification, and time series analysis. There is now an expanded treatment of resampling tests and key analysis techniques, an updated discussion on ensemble forecasting, and a detailed chapter on forecast verification. In addition, the book includes new sections on maximum likelihood and on statistical simulation and contains current references to original research. Students will benefit from pedagogical features including worked examples, end-of-chapter exercises with separate solutions, and numerous illustrations and equations. This book will be of interest to researchers and students in the atmospheric sciences, including meteorology, climatology, and other geophysical disciplines. Accessible presentation and explanation of techniques for atmospheric data summarization, analysis, testing and forecasting Many worked examples End-of-chapter exercises, with answers provided

## Statistics Explained

*An Introductory Guide for Life Scientists*

**Author**: Steve McKillup

**Publisher:**Cambridge University Press

**ISBN:**1139502948

**Category:**Medical

**Page:**N.A

**View:**4769

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An understanding of statistics and experimental design is essential for life science studies, but many students lack a mathematical background and some even dread taking an introductory statistics course. Using a refreshingly clear and encouraging reader-friendly approach, this book helps students understand how to choose, carry out, interpret and report the results of complex statistical analyses, critically evaluate the design of experiments and proceed to more advanced material. Taking a straightforward conceptual approach, it is specifically designed to foster understanding, demystify difficult concepts and encourage the unsure. Even complex topics are explained clearly, using a pictorial approach with a minimum of formulae and terminology. Examples of tests included throughout are kept simple by using small data sets. In addition, end-of-chapter exercises, new to this edition, allow self-testing. Handy diagnostic tables help students choose the right test for their work and remain a useful refresher tool for postgraduates.

## Introduction to Information Retrieval

**Author**: Christopher D. Manning,Prabhakar Raghavan,Hinrich Schütze

**Publisher:**Cambridge University Press

**ISBN:**1139472100

**Category:**Computers

**Page:**N.A

**View:**4865

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Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

## Statistical Tables

**Author**: F. James Rohlf,Robert R. Sokal

**Publisher:**Macmillan

**ISBN:**9780716724124

**Category:**Science

**Page:**199

**View:**9853

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This separate compendium of tables used with Sokal/Rohlf, Biometry, Third Edition, eliminates the inconvenience of having to turn back and forth within the text to refer to data. It can also be used with other texts, or as an independent research resource.

## Statistics with Confidence

*Confidence Intervals and Statistical Guidelines*

**Author**: Douglas Altman,David Machin,Trevor Bryant,Martin Gardner

**Publisher:**John Wiley & Sons

**ISBN:**1118702506

**Category:**Medical

**Page:**256

**View:**2555

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This highly popular introduction to confidence intervals has been thoroughly updated and expanded. It includes methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice.