free statistical books

Time-Series Analysis and Cyclostratigraphy: Examining Stratigraphic Records of Environmental Cycles
By Graham P. Weedon


Publisher: Cambridge University Press
Number Of Pages: 274
Publication Date: 2003-02-17
ISBN-10 / ASIN: 0521620015
ISBN-13 / EAN: 9780521620017
Binding: Hardcover


Product Description:

Increasingly, environmental scientists, palaeoceanographers and geologists are collecting quantitative records of environmental changes (time series) from sediments, ice cores, cave calcite, corals and trees. This book explains how to analyze these records, using straightforward explanations and diagrams rather than formal mathematical derivations. All the main cyclostratigraphic methods are covered, including spectral analysis, cross-spectral analysis, filtering, complex demodulation, and wavelet and singular spectrum analysis. Practical problems of time-series analysis are considered in detail. Recent research into various types of tidal and climatic cycles is summarized.

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Time-Series Analysis and Cyclostratigraphy: Examining Stratigraphic Records of Environmental Cycles
By Graham P. Weedon


Publisher: Cambridge University Press
Number Of Pages: 274
Publication Date: 2003-02-17
ISBN-10 / ASIN: 0521620015
ISBN-13 / EAN: 9780521620017
Binding: Hardcover


Product Description:

Increasingly, environmental scientists, palaeoceanographers and geologists are collecting quantitative records of environmental changes (time series) from sediments, ice cores, cave calcite, corals and trees. This book explains how to analyze these records, using straightforward explanations and diagrams rather than formal mathematical derivations. All the main cyclostratigraphic methods are covered, including spectral analysis, cross-spectral analysis, filtering, complex demodulation, and wavelet and singular spectrum analysis. Practical problems of time-series analysis are considered in detail. Recent research into various types of tidal and climatic cycles is summarized.


7z -> pdf, 13M

Nonlinear Time Series
By Jianqing Fan, Qiwei Yao


Publisher: Springer
Number Of Pages: 576
Publication Date: 2003-03-12
ISBN-10 / ASIN: 0387951709
ISBN-13 / EAN: 9780387951706
Binding: Hardcover


Product Description:

This book presents the contemporary statistical methods and theory of nonlinear time series analysis. The principal focus is on nonparametric and semiparametric techniques developed in the last decade. It covers the techniques for modelling in state-space, in frequency-domain as well as in time-domain. To reflect the integration of parametric and nonparametric methods in analyzing time series data, the book also presents an up-to-date exposure of some parametric nonlinear models, including ARCH/GARCH models and threshold models. A compact view on linear ARMA models is also provided. Data arising in real applications are used throughout to show how nonparametric approaches may help to reveal local structure in high-dimensional data. Important technical tools are also introduced. The book will be useful for graduate students, application-oriented time series analysts, and new and experienced researchers. It will have the value both within the statistical community and across a broad spectrum of other fields such as econometrics, empirical finance, population biology and ecology. The prerequisites are basic courses in probability and statistics. Jianqing Fan, coauthor of the highly regarded book Local Polynomial Modeling, is Professor of Statistics at the University of North Carolina at Chapel Hill and the Chinese University of Hong Kong. His published work on nonparametric modeling, nonlinear time series, financial econometrics, analysis of longitudinal data, model selection, wavelets and other aspects of methodological and theoretical statistics has been recognized with the Presidents' Award from the Committee of Presidents of Statistical Societies, the Hettleman Prize for Artistic and Scholarly Achievement from the University of North Carolina, and by his election as a fellow of the American Statistical Association and the Institute of Mathematical Statistics. Qiwei Yao is Professor of Statistics at the London School of Economics and Political Science. He is an elected member of the International Statistical Institute, and has served on the editorial boards for the Journal of the Royal Statistical Society (Series B) and the Australian and New Zealand Journal of Statistics.


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3,45 MB

Secondary Analysis of the TIMSS Data
By David F. Robitaille, Albert E. Beaton


Publisher: Springer
Number Of Pages: 440
Publication Date: 2002-09-30
ISBN-10 / ASIN: 1402008597
ISBN-13 / EAN: 9781402008597
Binding: Hardcover


Product Description:


The goal of this volume is to use the data from IEA's Third International Mathematics and Science Study (TIMSS) to investigate significant questions related to mathematics and science education as well as a number of methodological issues. The authors of the papers included in this collection come from eleven of the TIMSS countries, and they are prominent in their respective fields. The book will be of interest to readers interested in comparative education, mathematics and science education, curriculum, and survey research methodology.

A study such as TIMSS costs a great deal of money to carry out; and, if the true value of that investment is to be realized, much more research of the kind reported in this collection is needed. The papers included provide insights into the impact that TIMSS has had in the participating countries. They also serve as excellent examples of the kind of follow-up research that is needed.

17.712 MB rared pdf

Methods of Microarray Data Analysis II
By Simon M. Lin, Kimberly F. Johnson


Publisher: Springer
Number Of Pages: 232
Publication Date: 2002-06-30
ISBN-10 / ASIN: 1402071116
ISBN-13 / EAN: 9781402071119
Binding: Hardcover


Product Description:


Microarray technology is a major experimental tool for functional genomic explorations, and will continue to be a major tool throughout this decade and beyond. The recent explosion of this technology threatens to overwhelm the scientific community with massive quantities of data. Because microarray data analysis is an emerging field, very few analytical models currently exist. Methods of Microarray Data Analysis II is the second book in this pioneering series dedicated to this exciting new field. In a single reference, readers can learn about the most up-to-date methods, ranging from data normalization, feature selection, and discriminative analysis to machine learning techniques.

Currently, there are no standard procedures for the design and analysis of microarray experiments. Methods of Microarray Data Analysis II focuses on a single data set, using a different method of analysis in each chapter. Real examples expose the strengths and weaknesses of each method for a given situation, aimed at helping readers choose appropriate protocols and utilize them for their own data set. In addition, web links are provided to the programs and tools discussed in several chapters. This book is an excellent reference not only for academic and industrial researchers, but also for core bioinformatics/genomics courses in undergraduate and graduate programs.


7.42 MB rared pdf

Aspects of Multivariate Statistical Analysis in Geology
By R.A. Reyment, E. Savazzi


Publisher: Elsevier
Number Of Pages: 292
Publication Date: 1999-11-01
ISBN-10 / ASIN: 0444825681
ISBN-13 / EAN: 9780444825681
Binding: Hardcover


Product Description:

The book presents multivariate statistical methods useful in geological analysis. The essential distinction between multivariate analysis as applied to full-space data (measurements on lengths, heights, breadths etc.) and compositional data is emphasized with particular reference to geochemical data. Each of the methods is accompanied by a practically oriented computer program and backed up by appropriate examples. The computer programs are provided on a compact disk together with trial data-sets and examples of the output.


An important feature of this book is the graphical system developed by Dr. Savazzi which is entitled Graph Server. Geological data often deviate from ideal statistical requirements. For this reason, close attention has been paid to the analysis of data that contain atypical observations.

10.911 MB rared pdf

Pharmaceutical Statistics: Practical and Clinical Applications, Fourth Edition, Revised and Expanded (Drugs and the Pharmaceutical Sciences)
By Sanford Bolton, Charles Bon


Publisher: Informa HealthCare
Number Of Pages: 784
Publication Date: 2003-10-17
ISBN-10 / ASIN: 0824746953
ISBN-13 / EAN: 9780824746957
Binding: Hardcover


Product Description:

The fourth edition of this text includes a disk with special programs to aid in problem analysis. The text presents fresh material on concept conformity and release targets and describes linear regression and correlation, the analysis of variance and crossover designs.


4.462 MB rared pdf

Applied Latent Class Analysis
By Jacques A. Hagenaars, Allan L. McCutcheon


Publisher: Cambridge University Press
Number Of Pages: 476
Publication Date: 2002-06-24
ISBN-10 / ASIN: 0521594510
ISBN-13 / EAN: 9780521594516
Binding: Hardcover


Product Description:

This study introduces several recent innovations in latent class analysis to a wider audience of researchers. Many of the world's leading innovators in the field of latent class analysis have contributed essays to the volume, each presenting a key innovation to the basic LCM and illustrating how it can prove useful in situations typically encountered in actual research.

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Multivariate Analysis of Data in Sensory Science (Data Handling in Science and Technology) (Data Handling in Science and Technology)
By T. Næs, E. Risvik


Publisher: Elsevier Science
Number Of Pages: 364
Publication Date: 1996-02-01
ISBN-10 / ASIN: 0444899561
ISBN-13 / EAN: 9780444899569
Binding: Hardcover


Product Description:

The state-of-the-art of multivariate analysis in sensory science is described in this volume. Both methods for aggregated and individual sensory profiles are discussed. Processes and results are presented in such a way that they can be understood not only by statisticians but also by experienced sensory panel leaders and users of sensory analysis.

The techniques presented are focused on examples and interpretation rather than on the technical aspects, with an emphasis on new and important methods which are possibly not so well known to scientists in the field. Important features of the book are discussions on the relationship among the methods with a strong accent on the connection between problems and methods. All procedures presented are described in relation to sensory data and not as completely general statistical techniques.

Sensory scientists, applied statisticians, chemometricians, those working in consumer science, food scientists and agronomers will find this book of value.

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16,06 MB

World Population Prospects: The 2006 Revision - Comprehensive Tables (Population Studies)
By Department of Economic & Social Affairs


Publisher: United Nations
Number Of Pages: 793
Publication Date: 2007-06-30
ISBN-10 / ASIN: 9211514290
ISBN-13 / EAN: 9789211514292
Binding: Paperback


48794 K Pdf.Rar

Medical Statistics Made Easy (Harris, Medical Statistics Made Easy)
By Michael Harris, Gordon Taylor


Publisher: Informa Healthcare
Number Of Pages: 114
Publication Date: 2003-12-05
ISBN-10 / ASIN: 185996219X
ISBN-13 / EAN: 9781859962190
Binding: Paperback


Product Description:

It is not necessary to know how to do a statistical analysis to critically appraise a paper. However, it is necessary to have a grasp of the basics, of whether the right test has been used and how to interpret the resulting figures. Short, readable, and useful, this book provides the necessary, basic information without becoming bogged down in the mathematical detail that often puts so many readers off statistics. It covers all the ground necessary to critically evaluate the statistical elements of medical research papers in an approachable way. This book is designed for healthcare students and professionals who need a basic definition and knowledge of common statistical terms.

Epidemiology for the Uninitiated
By David Coggon, David Barker, Geoffrey Rose


Publisher: BMJ Books
Number Of Pages: 80
Publication Date: 2003-05-23
ISBN-10 / ASIN: 0727916041
ISBN-13 / EAN: 9780727916044
Binding: Paperback


Product Description:

This perennial bestseller is an ideal introductions to epidemiology in health care. The fifith editon retains the book's simplicity and brevity, at the same time providing the reader with the core elements of epidemiology needed in health care practice and research. The text has been revised throughout, with new examples introduced to bring the book right up to date.

A Beginner's Guide to Structural Equation Modeling
By Randall E. Schumacker, Richard G. Lomax


Publisher: Lawrence Erlbaum
Number Of Pages: 512
Publication Date: 2004-05
ISBN-10 / ASIN: 0805840176
ISBN-13 / EAN: 9780805840179
Binding: Hardcover


Product Description:

This revised edition is intended to give students and researchers a basic understanding of SEM, focusing on the conceptual steps one takes in analyzing theoretical models. SEM is useful in statistical methods courses in social science, education, busines

Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models (Texts in Statistical Science)
By Julian J. Faraway


Publisher: Chapman & Hall/CRC
Number Of Pages: 312
Publication Date: 2005-12-20
ISBN-10 / ASIN: 158488424X
ISBN-13 / EAN: 9781584884248
Binding: Hardcover


Product Description:

Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway's critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which situations each one applies. Following in those footsteps, Extending the Linear Model with R surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author's treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. To demonstrate the interplay of theory and practice, throughout the book the author weaves the use of the R software environment to analyze the data of real examples, providing all of the R commands necessary to reproduce the analyses. A supporting Web site at www.stat.lsa.umich.edu/~faraway/ELM holds all of the data described in the book. Statisticians need to be familiar with a broad range of ideas and techniques. This book provides a well-stocked toolbox of methodologies, and with its unique presentation of these very modern statistical techniques, holds the potential to break new ground in the way graduate-level courses in this area are taught.

Hidden Markov Models: Estimation and Control (Stochastic Modelling and Applied Probability)
By Robert J. Elliott, Lakhdar Aggoun, John B. Moore


Publisher: Springer
Number Of Pages: 380
Publication Date: 2008-10-23
ISBN-10 / ASIN: 0387943641
ISBN-13 / EAN: 9780387943640
Binding: Hardcover


Product Description:


As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including results on smoothing for linear Gaussian dynamics.

In Chapter 2 the derivation of the basic filters related to the Markov chain are each presented explicitly, rather than as special cases of one general filter. Furthermore, equations for smoothed estimates are given. The dynamics for the Kalman filter are derived as special cases of the authors’ general results and new expressions for a Kalman smoother are given. The Chapters on the control of Hidden Markov Chains are expanded and clarified. The revised Chapter 4 includes state estimation for discrete time Markov processes and Chapter 12 has a new section on robust control.


4.29 MB rar pdf

Fima C. Klebaner “Introduction to Stochastic Calculus with Applications"
Imperial College Press | 2005-06-30 | ISBN: 1860945554 | 432 pages | PDF | 2,6 Mb

This book presents a concise treatment of stochastic calculus and its applications. It gives a simple but rigorous treatment of the subject including a range of advanced topics, it is useful for practitioners who use advanced theoretical results. It covers advanced applications, such as models in mathematical finance, biology and engineering. Self-contained and unified in presentation, the book contains many solved examples and exercises. It may be used as a textbook by advanced undergraduates and graduate students in stochastic calculus and financial mathematics. It is also suitable for practitioners who wish to gain an understanding or working knowledge of the subject. For mathematicians, this book could be a first text on stochastic calculus; it is good companion to more advanced texts by a way of examples and exercises. For people from other fields, it provides a way to gain a working knowledge of stochastic calculus. It shows all readers the applications of stochastic calculus methods and takes readers to the technical level required in research and sophisticated modelling. This second edition contains a new chapter on bonds, interest rates and their options. New materials include more worked out examples in all chapters, best estimators, more results on change of time, change of measure, random measures, new results on exotic options, FX options, stochastic and implied volatility, models of the age-dependent branching process and the stochastic LotkaVolterra model in biology, non-linear filtering in engineering and five new figures.

Generalized Linear Models, Second Edition (Monographs on Statistics and Applied Probability)
Chapman & Hall/CRC | 1989-08-01 | ISBN: 0412317605 | 532 pages | PDF | 16 Mb

The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data. Today, it remains popular for its clarity, richness of content and direct relevance to agricultural, biological, health, engineering, and other applications. The authors focus on examining the way a response variable depends on a combination of explanatory variables, treatment, and classification variables. They give particular emphasis to the important case where the dependence occurs through some unknown, linear combination of the explanatory variables. The Second Edition includes topics added to the core of the first edition, including conditional and marginal likelihood methods, estimating equations, and models for dispersion effects and components of dispersion. The discussion of other topics-log-linear and related models, log odds-ratio regression models, multinomial response models, inverse linear and related models, quasi-likelihood functions, and model checking-was expanded and incorporates significant revisions. Comprehension of the material requires simply a knowledge of matrix theory and the basic ideas of probability theory, but for the most part, the book is self-contained. Therefore, with its worked examples, plentiful exercises, and topics of direct use to researchers in many disciplines, Generalized Linear Models serves as ideal text, self-study guide, and reference.

Algebraic Statistics: Computational Commutative Algebra in Statistics
Chapman & Hall/CRC | 2000-12-21 | ISBN: 1584882042 | 184 pages | PDF | 1,2 Mb

Written by pioneers in this exciting new field, Algebraic Statistics introduces the application of polynomial algebra to experimental design, discrete probability, and statistics. It begins with an introduction to Gröbner bases and a thorough description of their applications to experimental design. A special chapter covers the binary case with new application to coherent systems in reliability and two level factorial designs. The work paves the way, in the last two chapters, for the application of computer algebra to discrete probability and statistical modelling through the important concept of an algebraic statistical model. As the first book on the subject, Algebraic Statistics presents many opportunities for spin-off research and applications and should become a landmark work welcomed by both the statistical community and its relatives in mathematics and computer science.