Statistics Courses

New and Noteworthy Textbooks for Your

STATISTICSCOURSES

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Contents

Introductory Statistics and General References......3

Statistical Theory and Methods..............................4

Computational Statistics ......................................10

Biostatistics ..........................................................12

Statistical Genetics and Bioinformatics ................14

Statistics for Engineering and Physical Science ....15

Statistics for Finance ............................................17

Statistics for Biological Sciences ..........................21

Statistics for Social Science and Psychology ........22

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3

Introductory Statistics and General References

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Introduction toProbabilitywith TexasHold’emExamplesFrederic PaikSchoenbergUniversity of California, LosAngeles, USA

“… the laserlike focus of the examples and exercisessets this book apart from other probability textbooksat this level. … The book is incredibly wellresearched — examples are drawn from actual televised poker games, and many explorations of theprobabilities in play in a given game situation conclude with a sentence about what really happened, which is a nice touch.”

—Mark Bollman, MAA Reviews, February 2012

This classroom-tested book illustrates both standardand advanced probability topics using Texas Hold’em,rather than the typical balls in urns. The authorincludes examples of actual hands of Texas Hold’emfrom the World Series of Poker and other major tour-naments. A dedicated R package that simulates handsand tournaments is freely available from CRAN.

• Uses real examples of Texas Hold’em hands toillustrate various probability topics

• Discusses random walks and the arcsine laws

• Shows students how to use R tocompute/approximate probabilities and simulateTexas Hold’em hands or tournaments

• Covers important poker concepts, such as potand implied odds, the “fundamental theorem ofpoker,” and quantification of luck and skill

• Presents the results of an optimal strategy forsimplified poker games

• Includes exercises in each chapter, with selectedsolutions in an appendix

• Offers a dedicated R package on CRAN that sim-ulates hands and tournaments of Texas Hold’em

Figure slides available upon qualifying course adoption

Selected Contents:

Probability Basics. Counting Problems. ConditionalProbability and Independence. Expected Value andVariance. Discrete Random Variables. ContinuousRandom Variables. Collections of Random Variables.Simulation and Approximation Using Computers.Appendices. References and Suggested Reading.Index.

Catalog no. K11367, December 2011, 199 pp.Soft Cover, ISBN: 978-1-4398-2768-0$49.95 / £31.99Also available as an eBook

Introduction tothe Theory ofStatisticalInferenceHannelore LieroUniversity of Potsdam, Germany

Silvelyn ZwanzigUppsala University, Sweden

“… it provides in-depth explanations, complete withproofs, of how statistics works. … The book has sev-eral user-friendly aspects. One is the use of eightexample data sets to illustrate the theory through-out the text. This repeated use of the same examplesallows readers to focus their energy on applying atheoretical point under discussion to a familiarexample rather than having to first becomeacquainted with a new example. Another big help isthe detailed solutions provided for the problems thatappear at the end of each chapter. … Also helpful:Theoretical or difficult material that can be skippedis marked with an asterisk. … The text analyzes notjust methods one learns in a first statistics course,but alternatives as well. Each chapter is capped by afurther reading section that is at once comprehen-sive and concise.”

—David A. Huckaby, MAA Reviews, February 2012

This text presents concise yet complete coverage ofstatistical inference theory, focusing on the funda-mental classical principles. Unlike related textbooks, itcombines the theoretical basis of statistical inferencewith a useful applied toolbox that includes linearmodels.

• Presents a concise treatment of the main topicsof statistical inference and linear models

• Includes proofs and solutions to all examplesand problems

• Requires no prior knowledge of measure theory

• Illustrates theorems and concepts with cartoonsand applications to statistical models

Selected Contents:

Introduction. Statistical Model. Inference Principles.Estimation. Testing Hypotheses. Linear Model.Solutions. Bibliography. Index.

Catalog no. K12437, July 2011, 284 pp., Soft CoverISBN: 978-1-4398-5292-7, $72.95 / £31.99Also available as an eBook




4 Request Your Complimentary eBook or Print Exam Copy at www.crctextbooks.com

Intro Stats and General References Intro Stats and General References

Statistical Theory and Methods

A Whistle-StopTour ofStatisticsBrian S. EverittKing’s College, London, UK

This book introduces basic probability and statisticsthrough bite-size coverage of key topics. Designed asa revision aid and study guide, it describes key con-cepts from probability and statistics in self-containedsections. It also makes an excellent reference for non-statisticians who need an easy-to-follow reference forbasic statistical techniques. The text shows how statis-tics can be applied in the real world with examples,diagrams, and graphs to illustrate concepts.

Catalog no. K13590, December 2011, 211 pp.Soft Cover, ISBN: 978-1-4398-7748-7$41.95 / £26.99

New!

The R StudentCompanionBrian DennisUniversity of Idaho, Moscow,USA

This student-oriented manual describes how to use Rin college science and mathematics courses. It fea-tures fully developed exercises based around the mainprecalculus analysis skills needed in the standard col-lege general education courses in science and math.The author presents applications drawn from all sci-ence and social science areas and includes the mostoften used features of R on a reference card in theback of the book. In addition, each chapter provides aset of exercises of R calculations.

Catalog no. K13498, September 2012, 360 pp.Soft Cover, ISBN: 978-1-4398-7540-7$39.95 / £25.99

New!

The A-Z ofError-FreeResearchPhillip I. GoodConsultant, Huntington Beach,California, USA

This practical book begins with an overview ofwhen—and when not—to use statistics. It guides stu-dents through the planning and data collection phas-es and presents various data analysis techniques,including methods for sample size determination. Theauthor then covers techniques for developing modelsthat provide a basis for future research. He also dis-cusses reporting techniques to ensure research effortsget the proper credit. The book concludes with case-control and cohort studies. R code is included toimplement the methods.

Catalog no. K14287, August 2012, 269 pp.Soft Cover, ISBN: 978-1-4398-9737-9$49.95 / £31.99Also available as an eBook

PracticalMultivariateAnalysisFifth EditionAbdelmonem Afifi,Susanne May, andVirginia A. Clark

“I found the text enjoyable and easy to read. Theauthors provide a sufficient description of all themethodology for practical use. Each chapterincludes at least one real-world dataset analysis andthe software commands summary tables included atthe end of every chapter should be particularly help-ful to a practitioner of statistics. … I would recom-mend the text for practitioners of statistics …”

—Thomas J. Fisher, Journal of BiopharmaceuticalStatistics, 2012

Solutions manual available upon qualifying courseadoption

Catalog no. K10864, July 2011, 537 pp.ISBN: 978-1-4398-1680-6, $93.95 / £46.99Also available as an eBook






5



Coming soon!

UnderstandingAdvancedStatisticalMethodsPeter WestfallTexas Tech University, Lubbock,USA

Kevin S.S. HenningSam Houston State University, Huntsville, Texas, USA

Designed for students in all disciplines—whethersocial science, biological science, or physical science—this text introduces mathematical statistics, includingcalculus and probability, in intuitive, self-contained,and accessible ways. Simulations and computing areused throughout. The book discusses Bayesian statis-tics before frequentist statistics, thoroughly coverspopulations versus processes, integrates design andmeasurement with analysis, and emphasizes theunderstanding and use of statistical models as recipesfor producing data.

• Provides a unique and accessible scientificallybased introduction to mathematical statistics

• Emphasizes simulation and computing withmany data examples

• Presents the necessary concepts in calculus andprobability in a very intuitive way

• Includes numerous exercises, enabling use as acourse text or for self-study


Selected Contents:

Introduction: Probability, Statistics and Science.Random Variables and Their Probability Distributions.Probability Calculation and Simulation. IdentifyingDistributions. Conditional Distributions andIndependence. Marginal Distributions, JointDistributions, Independence, and Bayes’ Theorem.Sampling from Populations and Processes. ExpectedValue and the Law of Large Numbers. Functions ofRandom Variables: Their Distributions and ExpectedValues. Distributions of Totals. Estimation:Unbiasedness, Consistency, and Efficiency. TheLikelihood Function and Maximum LikelihoodEstimates. Bayesian Statistics. Frequentist StatisticalMethods. Are Your Results Explainable by ChanceAlone? Chi-Squared, Student’s t, and F-Distributions,with Applications. Likelihood Ratio Tests. Sample Sizeand Power. Robustness and NonparametricMethods.

Catalog no. K14873, April 2013, c. 528 pp.ISBN: 978-1-4665-1210-8, $79.95 / £44.99Also available as an eBook

Coming soon!

StatisticalTheoryA ConciseIntroductionFelix AbramovichTel Aviv University, Israel

Ya' Acov RitovThe Hebrew University ofJerusalem, Israel

This text presents a clear introduction to statistical the-ory for advanced undergraduate students taking astandard course in statistics. It details the main ele-ments and basic concepts of statistical theory, includ-ing parameter estimation, confidence intervals,hypothesis testing, Bayesian interference, and deci-sion theory. The book takes an examples-basedapproach with clear exposition of key topics and justthe right amount of mathematical formality. It alsoincludes numerous exercises to enhance students’understanding of the topics discussed.

• Presents a clear and concise introduction to the key topics of statistical theory

• Offers the right balance of exposition and mathematical formality

• Introduces topics with illustrative examples,avoiding a dry approach to the subject

• Includes numerous exercises to facilitate teaching or self-study

Selected Contents:

Introduction

Parameter Estimation

Confidence Intervals and Confidence Regions

Large-Sample Theory

Hypotheses Testing

Bayesian Inference

Elementary Decision Theory

Catalog no. K12383, April 2013, c. 320 pp.ISBN: 978-1-4398-5184-5, $49.95 / £31.99Also available as an eBook






New!

GeneralizedLinear MixedModelsModern Concepts,Methods andApplicationsWalter W. StroupUniversity of Nebraska–Lincoln,USA

This text presents an introduction to linear modelingusing the GLMM as an overarching conceptual frame-work. For students new to linear models, the bookhelps them see the big picture. It shows how linearmodels fit with the rest of the core statistics curricu-lum and points out the major issues that statisticalmodelers must consider.

• Provides a true introduction to linear modeling

• Emphasizes the connection between studydesign and all aspects of the model

• Includes a chapter on GLMM-based power andsample size assessment—a critical tool for cost-effective design of research studies

• Presents numerous examples using the SASGLIMMIX procedure

• Gives in-depth treatments of issues unique togeneralized and mixed linear modeling, includ-ing conditional versus marginal modeling, broadversus narrow inference space, and data versusmodel-scale inference and reporting

• Offers the data for all exercises as well as SASfiles for all examples at www.crcpress.com

Selected Contents:

PART I The Big Picture:Modeling Basics. DesignMatters. Setting the Stage. PART II Estimation andInference Essentials: Estimation. Inference, Part I:Model Effects. Inference, Part II: CovarianceComponents. PART III Working with GLMMs:Treatment and Explanatory Variable Structure.Multilevel Models. Best Linear Unbiased Prediction.Rates and Proportions. Counts. Time-to-Event Data.Multinomial Data. Correlated Errors, Part I: RepeatedMeasures. Correlated Errors, Part II: Spatial Variability.Power, Sample Size, and Planning. Appendices.References. Index.

Catalog no. K10775, September 2012, 555 pp.ISBN: 978-1-4398-1512-0, $89.95 / £57.99Also available as an eBook

AppliedCategorical andCount DataAnalysisWan Tang, Hua He, andXin M. TuUniversity of Rochester, NewYork, USA

This self-contained text explains how to perform thestatistical analysis of discrete data. It covers classic con-cepts and popular topics, along with modern areasthat include models for zero-modified count out-comes, parametric and semiparametric longitudinaldata analysis, reliability analysis, and methods for deal-ing with missing values. R, SAS, SPSS, and Stata pro-gramming codes are provided for all the examples,enabling students to immediately experiment withthe data.

• Shows students how statistical models for non-continuous responses are applied to real studies,emphasizing difficult and overlooked issuesalong the pathway from models to data

• Covers useful topics in modern-day clinical trialsand observation studies

• Presents a systematic treatment of instrumenta-tion and measurement models for latent con-structs

• Compares popular models for clustered data,such as GLMM and GEE/WGEE

• Gives an in-depth study of missing values andtheir impact on parametric and semiparametric(distribution-free) models

• Includes exercises at the end of each chapter,many real data examples, and sample program-ming codes in SAS, SPSS, and STATA for modelimplementations

• Provides codes and updates on a supportingwebsite

Selected Contents:

Introduction. Contingency Tables. Sets ofContingency Tables. Regression Models forCategorical Response. Regression Models for CountResponse. Loglinear Models for Contingency Tables.Analyses of Discrete Survival Time. Longitudinal DataAnalysis. Evaluation of Instruments. Analysis ofIncomplete Data. References. Index.

Catalog no. K10311, June 2012, 384 pp.ISBN: 978-1-4398-0624-1, $89.95 / £57.99Also available as an eBook




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New!

StationaryStochasticProcessesTheory andApplicationsGeorg LindgrenLund University, Sweden

“In many respects, Stationary Stochastic Processesis an updated and expanded version that has cap-tured much of the same spirit (and topics!) as theCramér and Leadbetter classic. While there havebeen a number of new and good books publishedrecently on spatial statistics, none cover some of thekey important topics such as sample path propertiesand level crossings in a comprehensive and under-standable fashion like Lindgren’s book. This book isrequired reading for all of my PhD students workingin spatial statistics and related areas.”

—Richard A. Davis, Columbia University

“Particularly appealing features of the book are itsnumerous examples and remarks (some providinginteresting historical background). The structure ofthe book is such that it can be recommended both asa classroom text and for individual study.”

—Don Percival, University of Washington

“Georg Lindgren’s new book is a most attractivepresentation of the theory and application of theseprocesses, with an emphasis on second-order prop-erties and Fourier methods. … it presents, honestlyand clearly, all mathematical ideas that are needed,accompanying them by motivation and interpreta-tion that keep the wider purpose in mind. … thebook is authoritative and stimulating, a worthychampion of the tradition of Cramér and Leadbetter… a rich, inspiring book, full of good sense and clar-ity, an outstanding text in this important field.”

—Clive Anderson, University of Sheffield

Selected Contents:

Some Probability and Process Background. SampleFunction Properties. Spectral Representations. LinearFilters — General Properties. Linear Filters — SpecialTopics. Classical Ergodic Theory and Mixing. VectorProcesses and Random Fields. Level Crossings andExcursions.

Catalog no. K15489, October 2012, 375 pp.ISBN: 978-1-4665-5779-6, $89.95 / £57.99Also available as an eBook

Coming soon!

Linear Algebraand MatrixAnalysis forStatisticsSudipto BanerjeeUniversity of Minnesota,Minneapolis, USA

Anindya RoyUniversity of Maryland Baltimore County, USA

“This beautifully written text is unlike any other instatistical science. It starts at the level of a firstundergraduate course in linear algebra and takesthe student all the way up to the graduate level,including Hilbert spaces. It is extremely well craftedand proceeds up through that theory at a very goodpace. The statistics chapters are added at just theright places to motivate the reader and illustrate thetheory. The book is compactly written and mathe-matically rigorous, yet the style is lively as well asengaging. This elegant, sophisticated work will serveupper level and graduate statistics education well.All and all a book I wish I could have written.”

—Jim Zidek, University of British Columbia

• Provides students with an understanding of themajor concepts that underlie linear algebra andmatrix analysis

• Takes a vector-space approach, enabling elegantproofs and a smooth transition to more complextopics

• Presents recent developments in fields as diverseas spatial statistics, machine learning, and socialnetwork analysis

• Requires no prior knowledge of linear algebra

• Includes exercises and examples of statisticalapplications

Selected Contents:

Basic Operations. Systems of Linear Equations. Moreon Linear Equations. Euclidean Spaces. The Rank of aMatrix. Complementary Subspaces. Orthogonality,Orthogonal Subspaces, and Projections. More onOrthogonality. Revisiting Linear Equations.Determinants. Eigenvalues and Eigenvectors.Quadratic Forms. Matrix and Vector Norms. HilbertSpaces. References.

Catalog no. K10023, July 2013, c. 416 pp.ISBN: 978-1-4200-9538-8, $79.95 / £49.99Also available as an eBook






Introduction toStatistical LimitTheoryAlan M. PolanskyNorthern Illinois University,DeKalb, USA

Helping students develop a good understanding ofasymptotic theory, this text provides a thorough yetaccessible treatment of common modes of conver-gence and their related tools used in statistics. Theauthor explains as much of the background materialas possible and incorporates detailed proofs andexplanations of the results. The text includes manyend-of-chapter exercises and experiments as well asnumerous examples that illustrate the application ofasymptotic theory to modern statistical problems. Asolutions manual is available upon qualifying courseadoption.

Catalog no. C6604, January 2011, 645 pp.ISBN: 978-1-4200-7660-8, $93.95 / £59.99Also available as an eBook

Principles ofUncertaintyJoseph B. KadaneCarnegie Mellon University,Pittsburgh, Pennsylvania, USA

Winner of the 2011DeGroot Prize

“In this remarkable book, Kadane begins at the mostrudimentary level, develops all the needed mathe-matics on the fly, and still manages to flesh out atleast the core of the whole story, slowly, thoughtful-ly, and rigorously, right up to graduate level. … theauthor always carefully selects [the theorems] toclarify the basic meaning of the subject and his ownviews concerning the pitfalls and subtleties of itsproper application. Highly recommended.”

—D.V. Feldman, CHOICE, February 2012

Catalog no. K12848, May 2011, 503 pp.ISBN: 978-1-4398-6161-5, $89.95 / £59.99Also available as an eBook

Applied TimeSeries AnalysisWayne A. Woodward,Henry L. Gray, and Alan C. Elliott

“The book contains many illustrative examples, the-orems with proofs, and applied and theoreticalproblems at the end of each chapter with real-lifeapplications. Also, the book looks at generatingrealisations of the mentioned time series models viasoftware packages such as GW-WINKS and R. Thebook’s material is very valuable and is well present-ed, so it represents a good reference at both under-graduate and postgraduate levels, and also a goodsource for all who are interested in time series analy-sis.”—Hassan S. Bakouch, Journal of Applied Statistics, 2012


NonparametricStatisticalInferenceFifth EditionJean Dickinson Gibbonsand Subhabrata ChakrabortiUniversity of Alabama,Tuscaloosa, USA

“… one of the best books available for a graduate(or advanced undergraduate) text …”

—Biometrics, September 2011

“This excellently presented book achieves its aim ofseeding the fundamentals of non-parametric infer-ence. … The book is undoubtedly well written andpresents a good balance of theory and applications.… I would strongly recommend this book to univer-sity libraries, teachers and undergraduate studentswho want to learn non-parametric inference in the-ory and practice.”

—Journal of the Royal Statistical Society, Series A, April 2011

Catalog no. C7619, July 2010, 650 pp.ISBN: 978-1-4200-7761-2, $99.95 / £66.99Also available as an eBook






9



Introduction toGeneral andGeneralizedLinear ModelsHenrik Madsen andPoul ThyregodTechnical University of Denmark,Lyngby

“It is well written, easy to read and the discussion ofthe examples is clear. As a complement there is a col-lection of slides for an introductory course on gener-al, generalized, and mixed effects models on thehomepage. This book has a good set of references …I recommend this book as one of the textbooks to bediscussed in a course for model building.”

—Clarice G.B. Demétrio, Biometrics, February 2012Ancillaries available on the book’s website

Catalog no. C9155, November 2010, 316 pp.ISBN: 978-1-4200-9155-7, $87.95 / £41.99Also available as an eBook

Design ofExperimentsAn IntroductionBased on LinearModelsMax MorrisIowa State University, Ames, USA

“Overall, this is a book that is easy to like, with gooddefinitions of designs, few typographical errors, andconsistent, straightforward explications of the mod-els … I can picture a lot of students using a textaimed at a broad market design course but whoneed to understand more about what is going onbehind the curtain. Morris’ text fills that gap verywell.”

—Gary W. Oehlert, Biometrics, May 2012Solutions manual available upon qualifying courseadoption

Catalog no. C9233, July 2010, 370 pp.ISBN: 978-1-58488-923-6, $93.95 / £62.99Also available as an eBook

Bayesian Ideasand DataAnalysisAn Introduction forScientists andStatisticiansRonald Christensen,Wesley O. Johnson,Adam J. Branscum, andTimothy E. Hanson

“… a very interesting introductory book, very wellorganised and has been written in a style that isextremely pleasant and enjoyable to read. Both thestatistical concepts and examples are very wellexplained. In conclusion, I highly recommend thisbook as both a M.S./Ph.D. course text and as anexcellent reference book for anyone interested inBayesian statistics. A copy of it should certainlyappear in every university or, even private, library.”

—Rolando de la Cruz, Journal of Applied Statistics, June 2012

Ancillaries available on the book’s website

Catalog no. K10199, July 2010, 516 pp.ISBN: 978-1-4398-0354-7, $72.95 / £48.99Also available as an eBook

Time SeriesModeling,Computation, andInferenceRaquel PradoUniversity of California, SantaCruz, USA

Mike WestDuke University, Durham, NorthCarolina, USA

“The authors systematically develop a state-of-the-art analysis and modeling of time series. … this bookis well organized and well written. The authors pres-ent various statistical models for engineers to solveproblems in time series analysis. Readers no doubtwill learn state-of-the-art techniques from thisbook.”—Hsun-Hsien Chang, Computing Reviews, March 2012

Ancillaries available on the book’s website

Catalog no. C9336, May 2010, 368 pp.ISBN: 978-1-4200-9336-0, $99.95 / £62.99Also available as an eBook







Computational Statistics

R for StatisticsPierre-Andre Cornillon,Arnaud Guyader,Francois Husson,Nicolas Jegou, Julie Josse, Maela Kloareg, Eric Matzner-Lober, andLaurent Rouvière

“[T]he book is accessible for statisticians of all levelsand areas of expertise as well as for novice andadvanced R users. … I recommend it for anyone whowants to learn about the why and how of the mostcommonly employed statistical methods and theirextensions.”

—Irina Kukuyeva, Journal of Statistical Software,November 2012

This text explores the use of R for classical statisticalanalysis. The first half of the book introduces R, datamanipulation and visualization, statistical models,graphics, and R programming. The second half pres-ents various statistical analysis techniques by firstintroducing the data example, then describing theproblem to solve, and finally conducting the analysisusing R. This example-based approach enables stu-dents to replicate the analyses using their own data.Some of the techniques covered include simpleregression, multiple regression, ANOVA, logisticregression, principal component analysis, and cluster-ing.

• Offers a basic introduction to the use of R forstatistics

• Includes detailed information on installing andgetting started with R

• Presents material on data visualization, graphics,and programming

• Uses an example-based approach to data analysis

• Provides code and data sets from CRAN

Selected Contents:

An Overview of R:Main Concepts. Preparing Data.R Graphics. Making Programs with R. StatisticalMethods: Introduction to the Statistical Methods. AQuick Start with R. Hypothesis Test. Regression.Analysis of Variance and Covariance. Classification.Exploratory Multivariate Analysis. Clustering.Appendix.

Catalog no. K13834, March 2012, 320 pp.Soft Cover, ISBN: 978-1-4398-8145-3$59.95 / £34.99Also available as an eBook

New!

The BUGS BookA PracticalIntroduction toBayesian AnalysisDavid Lunn, Chris Jackson, Nicky Best, Andrew Thomas, andDavid Spiegelhalter

“The most anticipated applied Bayesian text of thelast 20 years, The BUGS Book is like a wonderfulalbum by an established rock supergroup: the pres-sure to deliver a high-quality product was enormous,but the authors have created a masterpiece wellworth the wait. The book offers the perfect mix ofbasic probability calculus, Bayes and MCMC basics,an incredibly broad array of useful statistical mod-els, and a BUGS tutorial and user manual completewith all the ‘tricks’ one would expect from the teamthat invented the language. BUGS is the dominantBayesian software package of the post-MCMC eraand this book ensures it will remain so for years tocome by providing accessible yet comprehensiveinstruction in its proper use. A must-own for anyworking applied statistical modeler.”

—Bradley P. Carlin, University of Minnesota

• Provides an accessible, practical introduction toBayesian analysis using the BUGS software

• Covers all the functionalities of BUGS, includingprediction, missing data, model criticism, andprior sensitivity

• Features a large number of worked examplesand applications from a wide range of disciplines

• Includes detailed exercises and solutions on asupporting website

Selected Contents:

Introduction: Probability and Parameters. MonteCarlo Simulations using BUGS. Introduction toBayesian Inference. Introduction to Markov ChainMonte Carlo Methods. Prior Distributions. RegressionModels. Categorical Data. Model Checking andComparison. Issues in Modeling. HierarchicalModels. Specialized Models. DifferentImplementations of BUGS. Appendices. Bibliography.Index.

Catalog no. C8490, October 2012, 399 pp.Soft Cover, ISBN: 978-1-58488-849-9$49.95 / £24.99Also available as an eBook




11

Computational Statistics


StatisticalComputing inC++ and RRandall L. EubankArizona State University, Tempe,USA

Ana KupresaninLawrence Livermore NationalLaboratory, California, USA

Parallel processing can be ideally suited for the solvingof more complex problems in statistical computing.This book discusses code development in C++ and R,before going beyond to look at the valuable use ofthese two languages in unison. It covers linear equa-tion solution with regression and linear models moti-vation, optimization with maximum likelihood andnonlinear least squares motivation, and random num-ber generation. While the text does require a workingknowledge of basic concepts in statistics and experi-ence in programming, it does not require knowledgespecific to C++ or R.

• Integrates both C++ and R for the solution ofstatistical computing problems

• Covers object-oriented programming in bothlanguages

• Uses C++ code in R and R functions in the C++program

• Presents applications of the C++ StandardTemplate Library for statistical computing purposes

• Provides an introduction to parallel processing inC++ and R

Selected Contents:

Introduction. Computer Representation of Numbers.A Sketch of C++. Generation of Pseudo-RandomNumbers. Programming in R. Creating Classes andMethods in R. Numerical Linear Algebra. NumericalOptimization. Abstract Data Structures. DataStructures in C++. Parallel Computing in C++ and R.An Introduction to Unix. An Introduction to R. C++Library Extensions (TR1). The Matrix and VectorClasses. The ranGen Class. References. Index.

Catalog no. C6650, December 2011, 556 pp.ISBN: 978-1-4200-6650-0, $89.95 / £59.99Also available as an eBook

A GentleIntroduction to StataRevised Third EditionAlan C. AcockOregon State University,Corvallis, USA

Updated to reflect the new features of Stata 11, thisthird edition continues to help new Stata usersbecome proficient in Stata. After reading this intro-ductory text, students will be able to enter, build, andmanage a data set as well as perform fundamental sta-tistical analyses. This edition includes a new chapteron the analysis of missing data and the use of multi-ple-imputation methods. It also provides an extensiverevision of the chapter on ANOVA, along with addi-tional material on the application of power analysis.Each chapter includes exercises and real data sets.

• Reflects the new features of Stata 11

• Shows how to enter, build, and manage a dataset

• Supplements basic statistical modeling topicswith discussions of effect sizes and standardizedcoefficients

• Discusses various model selection criteria, suchas semipartial correlations

• Employs real data sets, such as the GeneralSocial Surveys from 2002 and 2006

Selected Contents:

Support Materials. Getting Started. Entering Data.Preparing Data for Analysis. Working withCommands, Do-Files, and Results. DescriptiveStatistics and Graphs for One Variable. Statistics andGraphs for Two Categorical Variables. Tests for Oneor Two Means. Bivariate Correlation and Regression.Analysis of Variance. Multiple Regression. LogisticRegression. Measurement, Reliability, and Validity.Working with Missing Values—Multiple Imputation.Appendix. References. Author Index. Subject Index.

Catalog no. N10594, March 2012, 401 pp.Soft Cover, ISBN: 978-1-59718-109-9$79.95 / £49.99





Biostatistics

New!

MedicalBiostatisticsThird EditionAbhaya IndrayanThe third edition of this acclaimed text focuses on thestatistical aspects of medicine, showing how biostatis-tics is a useful tool to manage some medical uncer-tainties. This edition describes several new topics,including adaptive designs, STROBE statement,dietary indices, measures of health inequality, Poissondistribution, path analysis, Six Sigma in health care,and much more. Along with software illustrations, italso expands coverage of survival analysis, ROCcurves, equivalence assessment, and repeated meas-ures ANOVA.

• Demonstrates how biostatistics can help managemany types of medical uncertainties

• Presents step-by-step explanations of statisticalmethods, along with a large number of real-lifeexamples and worked exercises

• Provides guide charts at the beginning of thebook to enable quick access of relevant statisticalprocedure

• Illustrates how statistical methods can be used tohandle various aspects of a medical researchsetup

Selected Contents:

Medical Uncertainties. Basics of Medical Studies.Sampling Methods. Designs of ObservationalStudies. Medical Experiments. Clinical Trials.Numerical Methods for Representing Variation.Presentation of Variation by Figures. SomeQuantitative Aspects of Medicine. Clinimetrics andEvidence-Based Medicine. Measurement ofCommunity Health. Confidence Intervals, Principlesof Tests of Significance, and Sample Size. Inferencefrom Proportions. Relative Risk and Odds Ratio.Inference from Means. Relationships: QuantitativeData. Relationships: Qualitative Dependent. SurvivalAnalysis. Simultaneous Consideration of SeveralVariables. Quality Considerations. Statistical Fallacies.

Catalog no. K13952, August 2012, 1024 pp., ISBN:978-1-4398-8414-0, $129.95 / £82.00Also available as an eBook

New!

RegressionModels as aTool in MedicalResearchWerner VachInstitute of Medical Biometry andMedical Informatics, Freiburg,Germany

While regression models have become standard toolsin medical research, understanding how to properlyapply the models and interpret the results is oftenchallenging for beginners. This text presents the fun-damental concepts and important aspects of regres-sion models most commonly used in medicalresearch, including the classical regression model forcontinuous outcomes, the logistic regression modelfor binary outcomes, and the Cox proportional haz-ards model for survival data. The author emphasizesadequate use, correct interpretation of results, appro-priate presentation of results, and avoidance of poten-tial pitfalls.

• Helps students improve their understanding ofthe role of regression models in the medical field

• Illustrates each technique with a concrete example, enabling students to better appreciatethe properties and theory of the methods

• Uses Stata to demonstrate the practical use ofthe models

• Discusses how and when regression models canfail

• Describes the basic principles behind statisticalcomputations, with more mathematical detailsgiven in the appendices

• Offers the data sets, solutions to all exercises,and a short introduction to Stata on the author’swebsite


Selected Contents:

The Basics. Advanced Topics and Techniques. RiskScores and Predictors. Miscellaneous. MathematicalDetails. Bibliography. Index.

Catalog no. K15111, November 2012, 495 pp.ISBN: 978-1-4665-1748-6, $89.95 / £57.99Also available as an eBook




13

Biostatistics


MultivariateSurvivalAnalysis andCompetingRisksMartin J. CrowderImperial College, University ofLondon, UK

This text introduces univariate survival analysis andextends it to the multivariate case. It also covers com-peting risks and counting processes and providesmany real-world examples, exercises, and R code. Thetext discusses survival data, survival distributions,frailty models, parametric methods, multivariate dataand distributions, copulas, continuous failure, para-metric likelihood inference, and non- and semi-para-metric methods.

• Provides a broad overview of multivariate survival analysis, competing risks, and countingprocesses

• Contains many real-world examples to illustratethe methodology

• Presents a clear style aimed at graduate studentsin statistics

• Offers a supporting R package for the analyses,with some code in the book

Selected Contents:

Univariate Survival Analysis: Survival Data. SurvivalDistributions. Frailty Models. Parametric Methods.Discrete Time: Non- and Semi-Parametric Methods.Continuous Time: Non- and Semi-ParametricMethods. Multivariate Survival Analysis:Multivariate Data and Distributions. Frailty andCopulas. Repeated Measure. Wear and Degradation.Competing Risks: Continuous Failure Times andTheir Causes. Parametric Likelihood Inference. LatentFailure Times: Probability Distributions. DiscreteFailure Times in Competing Risks. Hazard-BasedMethods for Continuous Failure Times. Latent FailureTimes: Identifiability Crises. Counting Processes inSurvival Analysis: Some Basic Concepts. SurvivalAnalysis. Non- and Semi-Parametric Methods.

Catalog no. K13489, April 2012, 417 pp.ISBN: 978-1-4398-7521-6, $99.95 / £63.99Also available as an eBook

BiostatisticsA ComputingApproachStewart AndersonUniversity of Pittsburgh,Pennsylvania, USA

Focusing on visualization and computationalapproaches with an emphasis on the importance ofsimulation, this book introduces modern and classicalbiostatistical methods and compares their respectiveusefulness. Assuming only basic knowledge of proba-bility and statistics, the text covers essential topics inbiostatistical science, offers numerous practical appli-cations and detailed worked examples taken from themedical arena (all computed using R and SAS), andincludes exercises with solutions.

Catalog no. C8342, December 2011, 326 pp.ISBN: 978-1-58488-834-5, $83.95 / £41.99Also available as an eBook

Exercises andSolutions inBiostatisticalTheoryLawrence L. Kupper,Brian Neelon, and Sean M. O’Brien

“Overall, I like this book very much. The problemsare carefully chosen and cover a wide range of real-world applications of biostatistical methods.Instructors and students will find this book to be agood source of supplementary problems for practice.… I have taught courses in mathematical statisticson several prior occasions and wish a book like thiswas available earlier.”

—Kaushik Ghosh, Journal of Biopharmaceutical Statistics, 2012

Catalog no. C7222, November 2010, 420 pp.Soft Cover, ISBN: 978-1-58488-722-5$54.95 / £25.99Also available as an eBook






Statistical Genetics and Bioinformatics

StochasticModelling forSystems BiologySecond EditionDarren J. WilkinsonNewcastle University, UK

This text provides an accessible introduction to theuse of stochastic processes for modeling biologicalsystems, such as genetic and biochemical networks.Focusing on simulation, the text includes many exam-ples, R and SBML code, and a number of computer-based exercises.

Fully updated, this second edition includes improve-ments to the chapters on Markov processes, kinetics,and approximate algorithms. It also greatly expandsthe coverage of statistical inference using likelihood-free techniques. Updated computing aspects include anew R package and the use of the new SBML Level 3.

• Provides an accessible introduction to stochasticmodeling for systems biology

• Focuses on computer simulation, with R andSBML code

• Includes many biologically motivated examples

• Presents enhanced material on statistical inference

• Contains exercises and further reading in eachchapter

Selected Contents:

Modeling and Networks: Introduction to BiologicalModeling. Representation of Biochemical Networks.Stochastic Processes and Simulation: ProbabilityModels. Stochastic Simulation. Markov Processes.Stochastic Chemical Kinetics: Chemical andBiochemical Kinetics. Case Studies. Beyond theGillespie Algorithm. Bayesian Inference: BayesianInference and MCMC. Inference for StochasticKinetic Models. Conclusions: SBML Models.


Statistics andData Analysisfor MicroarraysUsing R andBioconductorSecond Edition Sorin DrăghiciWayne State University, Detroit,Michigan, USA

This richly illustrated text provides a clear and rigorousdescription of powerful analysis techniques and algo-rithms for mining and interpreting biological informa-tion. It takes a hands-on, example-based approachthat explains the basics of R and microarray technolo-gy as well as how to choose and apply the proper dataanalysis tool to specific problems. This updated andexpanded edition includes 14 new chapters and offersthe R code on a CD-ROM.

• Presents an in-depth treatment of the statisticaland data analysis aspects used in microarraysand bioinformatics

• Provides the option of learning R in parallel withlearning about data analysis

• Covers background material for those with alimited mathematical, genetic, or molecular biology foundation

• Includes R code on a CD-ROM

Selected Contents:

The Cell and Its Basic Mechanisms. Microarrays.Reliability and Reproducibility Issues in DNAMicroarray Measurements. Image Processing.Introduction to R. Bioconductor: Principles andIllustrations. Elements of Statistics. ProbabilityDistributions. Basic Statistics in R. StatisticalHypothesis Testing. Classical Approaches to DataAnalysis. ANOVA. Linear Models in R. ExperimentDesign. Multiple Comparisons. Analysis andVisualization Tools. Cluster Analysis. Quality Control.Data Pre-Processing and Normalization. Methods forSelecting Differentially Regulated Genes. The GeneOntology (GO). Functional Analysis and BiologicalInterpretation of Microarray Data. Uses, Misuses, andAbuses in GO Profiling. A Comparison of SeveralTools for Ontological Analysis. Focused Microarrays— Comparison and Selection. ID Mapping Issues.Pathway Analysis. Machine Learning Techniques. TheRoad Ahead. References.

Catalog no. K10487, December 2011, 1036 pp.ISBN: 978-1-4398-0975-4, $89.95 / £57.99Also available as an eBook




15

Statistics for Engineering and Physical Science


Probability,Statistics, andReliability forEngineers andScientistsThird EditionBilal M. Ayyub andRichard H. McCuenUniversity of Maryland, CollegePark, USA

The third edition of this bestselling text presents prob-ability, statistics, reliability, and risk methods with anideal balance of theory and applications. It placesincreased emphasis on simulation as a modeling tool,applying it progressively with projects that continue ineach chapter. This edition also features expanded dis-cussions of ANOVA and a thorough treatment ofMonte Carlo simulation. The authors not only estab-lish the limitations, advantages, and disadvantages ofeach method, but also show that data analysis is acontinuum rather than the isolated application of dif-ferent methods.

• Emphasizes risk and reliability for practical engineering applications

• Provides additional material on simulation, themathematics related to uncertainty, the randfunction, sample variability, dependence, thePoisson process, and more

• Contains more illustrations on histogram sam-ples and hypothesis testing along with Venn diagrams for conditional probabilities

Solutions manual and PowerPoint slides availableupon qualifying course adoption

Selected Contents:

Introduction. Data Description and Treatment.Fundamentals of Probability. Probability Distributionsfor Discrete Random Variables. ProbabilityDistributions for Continuous Random Variables.Multiple Random Variables. Simulation.Fundamentals of Statistical Analysis. HypothesisTesting. Analysis of Variance. Confidence Intervalsand Sample Size Determination. Regression Analysis.Multiple and Nonlinear Regression Analysis.Reliability Analysis of Components. Reliability andRisk Analysis of Systems. Bayesian Methods.Appendices. Index.

Catalog no. K10476, April 2011, 663 pp.ISBN: 978-1-4398-0951-8, $119.95 / £76.99Also available as an eBook

AppliedReliabilityThird EditionPaul A. TobiasRetired, Austin, Texas, USA

David C. TrindadeBloom Energy

This popular, easy-to-use guide addresses basicdescriptive statistics, reliability concepts, exponentialdistribution, Weibull distribution, and lognormal dis-tribution. It also covers reliability data plotting, accel-eration models, life test data analysis and systemsmodels, and much more. This third edition includes anew chapter on Bayesian reliability analysis as well asexpanded, updated coverage of repairable systemmodeling. Taking a practical and example-orientedapproach to reliability analysis, the book providesdetailed illustrations of software implementationthroughout using several widely available softwarepackages.

• Presents a practical and example-orientedapproach suitable for engineering and statisticsstudents

• Describes implementation of the methods usingstatistical software

• Emphasizes the powerful methodology of MLE

• Provides detailed graphical explanations ofmethods

• Offers software and other files on the book’sCRC Press web page

Selected Contents:

Basic Descriptive Statistics. Reliability Concepts.Exponential Distribution. Weibull Distribution. TheNormal and Lognormal Distributions. Reliability DataPlotting. Analysis of Multicensored Data. PhysicalAcceleration Models. Alternative Reliability Models.System Failure Modeling: Bottom-Up Approach.Quality Control in Reliability: Applications of DiscreteDistributions. Repairable Systems Part I:Nonparametric Analysis and Renewal Processes.Repairable Systems Part II: Nonrenewal Processes.Bayesian Reliability Evaluation. Answers to SelectedExercises. References. Index.

Catalog no. C4665, August 2011, 600 pp.ISBN: 978-1-58488-466-8, $93.95 / £63.99Also available as an eBook





Statistics for Engineering and Physical Science

ProbabilityFoundations forEngineersJoel A. NachlasVirginia Polytechnic Institute andState University, Blacksburg, USA

“… an excellent introductory book … it will preparethe IE, CE, and EE students for advanced coursesthat deal with random processes.”

—Edward A. Pohl, University of Arkansas

“… perfect for undergraduate engineering studentslooking for a textbook on probability.”

—Uday Kumar, Luleå University of Technology

“… an in-depth and rigorous presentation of proba-bility theory … The approach of using everydayengineering intuition to introduce the basic notionsof probabilities theory should make this book a valu-able tool for engineering students who want to learnthe basic concepts and notions of probability theoryand to be able to make use of these in engineeringproblems.”

—Christophe Bereguer, Grenoble Institute ofTechnology

“… this book takes a fresh approach to teachingundergraduate engineering students the fundamen-tals of probability. … Students should be better ableto retain the knowledge gained through reading thistext because of the relevance of the examples andapplications.”

—Lisa Maillart, University of Pittsburgh

Solutions manual and PowerPoint slides upon qualifying course adoption

Selected Contents:

Historical Perspectives. A Brief Review of Set Theory.Probability Basics. Random Variables andDistributions. Joint, Marginal, and ConditionalDistributions. Expectation and Functions of RandomVariables. Moment-Generating Functions.Approximations and Limiting Behavior. Appendix.Index.


Statistical andEconometricMethods forTransportationData AnalysisSecond EditionSimon P. Washington,Matthew G. Karlaftis,and Fred L. Mannering

“The second edition introduces an especially broadset of statistical methods, which are useful not onlyfor transportation modeling but also for modeling inother disciplines. … an excellent textbook foradvanced undergraduate, master’s, and Ph.D. stu-dents, covering topics from simple descriptive statis-tics to complex Bayesian models. … one of the fewbooks that covers an extensive set of statisticalmethods needed for data analysis in transporta-tion.”—Itzhak Ditzian, The American Statistician, November

2011

With many examples and case studies, this update ofa bestseller provides an understanding of a broadrange of analytical tools required to solve transporta-tion problems. This second edition includes newchapters on logistic regression, ordered probabilitymodels, random-parameter models, and Bayesian sta-tistical modeling. Data sets and instructor materialsare available on the book’s CRC Press web page.

Selected Contents:

FUNDAMENTALS: Statistical Inference I: DescriptiveStatistics. Statistical Inference II: Interval Estimation,Hypothesis Testing, and Population Comparisons.CONTINUOUS DEPENDENT VARIABLE MODELS:Linear Regression. Violations of RegressionAssumptions. Simultaneous-Equation Models. PanelData Analysis. Background and Exploration in TimeSeries. Forecasting in Time Series: AutoregressiveIntegrated Moving Average (ARIMA) Models andExtensions. Latent Variable Models. Duration Models.COUNT AND DISCRETE DEPENDENT VARIABLEMODELS: Count Data Models. Logistic Regression.Discrete Outcome Models. Ordered ProbabilityModels. Discrete/Continuous Models. OTHER STA-TISTICAL METHODS: Random-Parameter Models.Bayesian Models. Appendices. References. Index.

Catalog no. C285X, December 2010, 544 pp.ISBN: 978-1-4200-8285-2, $104.95 / £69.99Also available as an eBook




17

Stats for Eng. and Physical Science Statistics for Finance


TransportationStatistics andMicrosimulationClifford Spiegelman,Eun Sug Park, andLaurence R. RilettBy discussing statistical concepts in the context oftransportation planning and operations, this text pro-vides the necessary background for making informedtransportation-related decisions. It explains the whybehind standard methods and uses real-world trans-portation examples and problems to illustrate keyconcepts. The book covers the statistical techniquesmost frequently employed by transportation andpavement professionals.

• Includes realistic transportation-related problemsthat draw on data from various U.S. transporta-tion studies

• Compares planned experiments, quasi-experiments, and field studies

• Presents strategies for conducting computer-aided statistical designs, fractional factorialdesigns, and screening designs

• Emphasizes bias-corrected confidence intervals

• Covers resampling techniques for evaluatinguncertainties, including the jackknife and bootstrap

• Takes a conjugate prior approach to Bayesianestimation

• Discusses smoothing estimators in both regression and density estimation

Selected Contents:

The Role of Statistics in Transportation Engineering.Graphical Methods for Displaying Data. NumericalSummary Measures. Probability and RandomVariables. Common Probability Distributions.Sampling Distributions. Inferences: HypothesisTesting and Interval Estimation. Other InferentialProcedures: ANOVA and Distribution-Free Tests.Inferences Concerning Categorical Data. LinearRegression. Regression Models for Count Data.Experimental Design. Cross-Validation, Jackknife, andBootstrap Methods for Obtaining Standard Errors.Bayesian Approaches to Transportation Data Analysis.Microsimulation. Appendix.


New!

A Course onStatistics forFinanceStanley L. ScloveUniversity of Illinois, Chicago,USA

This text presents statistical methods for financialinvestment analysis. Providing the connectionbetween elementary statistics courses and quantita-tive finance courses, the book helps both existing andfuture quants improve their data analysis skills andbetter understand the modeling process. It incorpo-rates both applied statistics and mathematical statis-tics and requires no prior background in finance. Theauthor introduces regression analysis, time seriesanalysis, and multivariate analysis step by step usingmodels and methods from finance.

• Incorporates both applied statistics and mathematical statistics

• Covers fundamental statistical concepts andtools, including averages, measures of variability,histograms, non-numerical variables, rates ofreturn, and univariate, multivariate, two-way,and seasonal data sets

• Presents a careful development of regression,from simple to more complex models

• Integrates regression and time series analysiswith applications in finance

• Requires no prior background in finance

• Includes many exercises within and at the end of each chapter


Selected Contents:

INTRODUCTORY CONCEPTS AND DEFINITIONS:Review of Basic Statistics. Stock Price Series and Ratesof Return. Several Stocks and Their Rates of Return.REGRESSION: Simple Linear Regression; CAPM andBeta. Multiple Regression and Market Models. PORT-FOLIO ANALYSIS: Mean-Variance Portfolio Analysis.Utility-Based Portfolio Analysis. TIME SERIES ANALY-SIS: Introduction to Time Series Analysis. RegimeSwitching Models. Appendices. Index.

Catalog no. K14149, December 2012, 269 pp.ISBN: 978-1-4398-9254-1, $89.95 / £57.99Also available as an eBook





Statistics for Finance

Monte CarloSimulation withApplications toFinanceHui WangBrown University, Providence,Rhode Island, USA

Developed from the author’s course on Monte Carlosimulation at Brown University, this text provides aself-contained introduction to Monte Carlo methodsin financial engineering. It covers common variancereduction techniques, the cross-entropy method, andthe simulation of diffusion process models. Requiringminimal background in mathematics and finance, thebook includes numerous examples of option pricing,risk analysis, and sensitivity analysis as well as manyhand-and-paper and MATLAB® coding exercises at theend of every chapter.

• Presents common variance reduction techniquesas well as the cross-entropy method

• Covers the simulation of diffusion process models

• Requires minimal background in mathematicsand finance

• Contains numerous examples of option pricing,risk analysis, and sensitivity analysis

• Includes many hand-and-paper and MATLABcoding exercises at the end of every chapter

Selected Contents:

Review of Probability. Brownian Motion. ArbitrageFree Pricing. Monte Carlo Simulation. GeneratingRandom Variables. Variance Reduction Techniques.Importance Sampling. Stochastic Calculus.Simulation of Diffusions. Sensitivity Analysis.Appendices. Bibliography. Index.


An Introductionto ExoticOption PricingPeter BuchenUniversity of Sydney, Australia

In an easy-to-understand, nontechnical yet mathe-matically elegant manner, this book shows how toprice exotic options, including complex ones, withoutperforming complicated integrations or formally solv-ing PDEs. It develops special pricing techniques basedon the no-arbitrage principle and fully derives everyprice formula for the exotic options. The author incor-porates a significant amount of original, previouslyunpublished material and demystifies many esotericissues underpinning the mathematical treatment ofthe subject.

• Fully derives every price formula for the exoticoptions

• Develops special pricing techniques based onthe no-arbitrage principle

• Contains a significant amount of original, previously unpublished material, such as the use of log-volutions and Mellin transforms tosolve the Black-Scholes PDE

• Demystifies many esoteric issues underpinningthe mathematical treatment of the subject

• Includes challenging problems at the end ofeach chapter to illustrate the special pricingtechniques


Selected Contents:

Technical Background: Financial Preliminaries.Mathematical Preliminaries. Gaussian RandomVariables. Applications to Exotic Option Pricing:Simple Exotic Options. Dual Expiry Options. Two-Asset Rainbow Options. Barrier Options. LookbackOptions. Asian Options. Exotic Multi-Options.References. Index.

Catalog no. C9100, February 2012, 296 pp.ISBN: 978-1-4200-9100-7, $79.95 / £49.99Also available as an eBook




19



New!

ComputationalMethods inFinanceAli HirsaCaspian Capital Management,LLC, New York, USA

“A natural polymath, the author is at once ateacher, a trader, a quant, and now an author of abook for the ages. The content reflects the author’svast experience teaching master’s level courses atColumbia and NYU, while simultaneously research-ing and trading on quantitative finance in leadingbanks and hedge funds.”

—Peter Carr, Morgan Stanley and NYU CourantInstitute of Mathematical Sciences

“A long-time expert in computational finance, AliHirsa brings his excellent expository skills to bear onnot just one technique but the whole panoply, fromfinite difference solutions to PDEs/PIDEs throughsimulation to calibration and parameter estima-tion.”—Emanuel Derman, Columbia University and author

of Models Behaving Badly

Helping students accurately price a vast array of deriv-atives, this self-contained text explains how to solvecomplex functional equations through numericalmethods. It addresses key computational methods infinance, including transform techniques, the finite dif-ference method, and Monte Carlo simulation. It alsocovers model calibration and optimization anddescribes techniques, such as Kalman and particle fil-ters, for parameter estimation.

Selected Contents:

Pricing and Valuation: Stochastic Processes andRisk-Neutral Pricing. Derivatives Pricing via TransformTechniques. Introduction to Finite Differences.Derivative Pricing via Numerical Solutions of PDEs.Derivative Pricing via Numerical Solutions of PIDEs.Simulation Methods for Derivatives Pricing.Calibration and Estimation:Model Calibration.Filtering and Parameter Estimation. References.Index.


OptionValuationA First Course inFinancialMathematicsHugo D. JunghennThe George WashingtonUniversity, Washington, D.C.,USA

Largely self-contained, this classroom-tested text pro-vides a straightforward introduction to the mathe-matics and models used in the valuation of financialderivatives. It examines the principles of option pric-ing in detail via standard binomial and stochastic cal-culus models and develops the requisite mathematicalbackground as needed. Numerous examples andexercises help students gain expertise with financialcalculus methods and increase their general mathe-matical sophistication.

• Offers a straightforward account of the principles and models of option pricing

• Focuses on the (discrete time) binomial modeland the (continuous time) Black-Scholes-Mertonmodel

• Develops probability theory and finance theoryfrom first principles

• Covers various types of financial derivatives,including currency forwards, put and calloptions, and path-dependent options (Asian,lookback, and barrier options)

• Illustrates the similarities and differencesbetween classical calculus and stochastic calculus

• Presents a martingale approach to option pricing

• Contains many examples and end-of-chapterexercises


Selected Contents:

Interest and Present Value. Probability Spaces.Random Variables. Options and Arbitrage. Discrete-Time Portfolio Processes. Expectation of a RandomVariable. The Binomial Model. ConditionalExpectation and Discrete-Time Martingales. TheBinomial Model Revisited. Stochastic Calculus. TheBlack-Scholes-Merton Model. Continuous-TimeMartingales. The BSM Model Revisited. OtherOptions. Appendices. Bibliography. Index.







StochasticFinanceA NumeraireApproachJan VecerColumbia University, New York,New York, USA

“… this book can be regarded as a wonderful appli-cation of stochastic analysis, as it includes not onlydetailed theoretical proofs but also practical illustra-tive examples. With the systematic and feasiblenumeraire techniques, the book can serve as aneveryday reference book for practitioners, but also asa powerful tool to deal with pricing and hedging forcomplicated financial assets. Most importantly, therepresentation of prices as a pairwise relationship oftwo assets is the most novel characteristic of thisbook, which could lead to deeper understanding ofderivative contracts.”

—Jian Ping Wan, Mathematical Reviews, 2012f

“Finally, we have a full volume with a systematictreatment of the change of numeraire techniques.Jan Vecer has taken years of teaching experience andpractitioners’ feedback to unify a previously compli-cated topic into the most elegant and easily accessi-ble numeraire textbook to come down the pike. Nowit has become fun to learn about parity and dualityrelationships among exotic options in a whole vari-ety of models. Practitioners will be happy about thedimension reduction methods. There should be moresuch books.”

—Uwe Wystup, MathFinance AG

Selected Contents:

Introduction. Elements of Finance. Binomial Model.Diffusion Models. Interest Rate Contracts. BarrierOptions. Lookback Options. American Options.Contracts on Three or More Assets: Quantos,Rainbows and "Friends". Asian Options. JumpModels. Appendix. Solutions to Selected Exercises.References. Index.

Catalog no. K10632, January 2011, 342 pp.ISBN: 978-1-4398-1250-1, $72.95 / £46.99Also available as an eBook

Coming soon!

QuantitativeFinanceAn Object-OrientedApproach in C++Erik SchloglUniversity of Technology, Sydney, Australia

This practical textbook builds a foundation in the keymethods and models of quantitative finance from theperspective of their implementation in C++. It intro-duces computational finance in a pragmatic manner,focusing on practical implementation. The authortakes an object-oriented approach that starts fromsimple building blocks for assembling more complexand powerful models. Models and algorithms areexpressed in the industry-standard C++ language.Working C++ source code is available on an accom-panying CD-ROM.

• Presents quantitative finance in a pragmaticmanner with a focus on practical implementation

• Serves as a self-contained reference for theimplementation of the key models and methods

• Expresses models and algorithms in the industry-standard programming language C++

• Takes an object-oriented approach, starting fromsimple building blocks and progressing to morecomplex and powerful models

• Provides working C++ source code on a CD-ROM

Selected Contents:

A Brief Review of the C++ Programming Language.Basic Building Blocks. Portfolio Optimization andAsset Pricing. Lattice Models. The Black-ScholesWorld. Finite Difference Methods for PartialDifferential Equations. Implied Volatility and ImpliedDistributions. Monte Carlo Simulation. The Heath-Jarrow-Morton Model. The Lognormal Forward Rate“Market Models.” Case Studies of the Object-Oriented Approach.

Catalog no. C4797, June 2013, c. 506 pp.ISBN: 978-1-58488-479-8, $79.95 / £49.99Also available as an eBook




21

Statistics for Biological Sciences


Introduction toStatistical DataAnalysis for theLife SciencesClaus Thorn Ekstrømand Helle SørensenUniversity of Copenhagen,Denmark

“This book can be a valuable assistance for studentsof life sciences and the other biological faculties andit can be treated both as a first handbook to statis-tical methods as well as a suitable tool to system-atize earlier experiences. … The book is written in aclear and engaging style. The authors put muchemphasis on the modelling part of statistical analy-sis and on biological interpretation of obtainedresults. It could be recommended for students butalso other readers looking for a handbook of ‘prac-tical’ statistics.”—Ewa Skotarczak, International Statistical Review, 2012

This text provides a computational toolbox thatenables students to perform actual analysis for realdata sets and gain the confidence and skills to under-take progressively more sophisticated analyses.Though accessible with any statistical software, thetext encourages a reliance on R. The authors providea short tutorial for those new to the software andinclude R commands and output at the end of eachchapter.

• Uses R software for exercises and examples

• Presents exercises with real data sets, which areaccessible from the book’s CRC Press web page

• Guides students through a proper analysis

• Includes solutions to selected exercises


Selected Contents:

Description of Samples and Populations. LinearRegression. Comparison of Groups. The NormalDistribution. Statistical Models, Estimation, andConfidence Intervals. Hypothesis Tests. ModelValidation and Prediction. Linear Normal Models.Probabilities. The Binomial Distribution. Analysis ofCount Data. Logistic Regression. Case Exercises.Appendices. Bibliography. Index.

Catalog no. K11221, August 2010, 427 pp.Soft Cover, ISBN: 978-1-4398-2555-6$72.95 / £33.99Also available as an eBook

Modelling andQuantitativeMethods inFisheriesSecond EditionMalcolm HaddonCSIRO, Hobart, Tasmania,Australia

“It is important to remember when reading thisbook that there are few texts that students can trulyconsult on fisheries science without a detailed under-standing of stock assessment and fisheries manage-ment practices—this text continues to bridge thatgap. The material has been revised and improve-ments made to a number of the examples. … Thebook is lavishly illustrated throughout with the useof Microsoft Excel workbooks, which adds to theflexibility, availability and ease of use of the text. Irecommend the text both as a course companionand for private study.”—Carl M. O’Brien, International Statistical Review, 2012

• Introduces an array of ideas in modeling andquantitative methods that have direct relevanceto fisheries science, biological modeling, ecolo-gy, and population dynamics

• Incorporates two new chapters on characterizinguncertainty and size-based models

• Includes many worked examples in Excel thathelp explain the analyses in detail and demon-strate how to perform the analyses

• Provides a set of example workbooks in Excel fordownload on the book’s CRC Press web page

Selected Contents:

Fisheries and Modeling. Simple Population Models.Model Parameter Estimation. Computer-IntensiveMethods. Randomization Tests. Statistical BootstrapMethods. Monte Carlo Modeling. Characterizationof Uncertainty. Growth of Individuals. StockRecruitment Relationships. Surplus ProductionModels. Age-Structured Models. Size-Based Models.Appendix. Bibliography. Index.

Catalog no. C561X, March 2011, 465 pp.ISBN: 978-1-58488-561-0, $83.95 / £41.99Also available as an eBook





Statistics for Social Science and Psychology

Modern Statistics for the Social and Behavioral SciencesA Practical IntroductionRand WilcoxUniversity of Southern California, Los Angeles, USA

• Covers standard methods as well as recentadvances and insights regarding when classicmethods perform well, and when and why theyare unsatisfactory

• Provides many examples using data from actualstudies, which illustrate the potential problemsassociated with methods routinely taught andused as well as the practical utility of moderntechniques.

• Offers over 900 R functions

• Includes solutions to selected exercises in anappendix

Selected Contents:

Introduction

Numerical and Graphical Summaries of Data

Probability and Related Concepts

Sampling Distributions and Confidence Intervals

Hypothesis Testing

Regression and Correlation

Bootstrap Methods

Comparing Two Independent Groups

Comparing Two Dependent Groups

One-Way ANOVA

Two-Way and Three-Way Designs

Comparing More Than Two Dependent Groups

Multiple Comparisons

Some Multivariate Methods

Robust Regression and Measures of Association

Basic Methods for Analyzing Categorical Data

Answers to Selected Exercises

Tables

Basic Matrix Algebra

References

Index

“This is an interesting and valuable book … Bygathering a mass of results on that topic into a sin-gle volume with references, alternative procedures,and supporting software, the author has provided avaluable service to those interested in these issues,which should probably include anyone teaching thetechniques covered in this book. … Recommended tothose with a solid background in traditional statisti-cal inference who want a highly competent andcomprehensive statement of the cases against tradi-tional statistical inference techniques.”

—Robert W. Hayden, MAA Reviews, March 2012

“Relative advantages/disadvantages of varioustechniques are presented so that the reader can behelped to understand the choices they make onusing the techniques. … A considerable number ofillustrations are included and the book focuses onusing R for its computer software application. … Auseful text for … postgraduate students in the socialscience disciplines.”—Susan Starkings, International Statistical Review, 2012

Designed for a two-semester, introductory course forgraduate students in the social sciences, this textintroduces three major insights in the field: 1) samplesize estimation needed to justify normality via the cen-tral limit theorem, 2) the impact of outliers and heavy-tailed distributions on power and our ability to obtainan accurate assessment of how groups differ and vari-ables are related, and 3) the deleterious effects of het-eroscedasticity on conventional ANOVA and regres-sion methods. Focusing on conceptual issues ratherthan complex computational details, it also provides alibrary of R functions for applying modern methodsthat effectively deal with these insights.

Requiring no prior training in statistics, the book pro-vides a graduate-level introduction to basic, routinelyused statistical techniques relevant to the social andbehavioral sciences. It describes methods developedduring the last 50 years that deal with known prob-lems associated with classic techniques. Espousing theview that no single method is always best, the textimparts a general understanding of the relative meritsof various techniques so that the choice of methodcan be made in an informed manner.

Catalog no. K11557, August 2011, 862 pp.ISBN: 978-1-4398-3456-5, $93.95 / £52.99Also available as an eBook



New from the Chapman & Hall/CRCTexts in Statistical Science Series

“This book is a unique blend of classical theory andapplication theory … The book is very well written,the themes are well chosen and the style is relaxedbut precise without being pedantic. My only regret isthat this book did not appear earlier! This book ishighly recommended!”

—Håvard Rue, Norwegian University of Science andTechnology


With numerous examples using SAS® PROC GLIMMIX,this book is ideal for graduate students in statistics. Itfocuses on data-driven processes and provides contextfor extending traditional linear model thinking to gen-eralized linear mixed modeling.


“… the authors have created a masterpiece wellworth the wait. The book offers the perfect mix ofbasic probability calculus, Bayes and MCMC basics,an incredibly broad array of useful statistical models,and a BUGS tutorial and user manual complete withall the ‘tricks’ one would expect from the team thatinvented the language. …”

—Bradley P. Carlin, University of Minnesota

Catalog no. C8490, October 2012, 399 pp., SoftCover, ISBN: 978-1-58488-849-9, $49.95 / £24.99Also available as an eBook

Developed from the authors’ graduate-level biostatis-tics course, this text explains how to perform the sta-tistical analysis of discrete data. The authors describethe basic ideas underlying each concept, model, andapproach to give students a good grasp of the funda-mentals of the methodology without using rigorousmathematical arguments.

Catalog no. K10311, June 2012, 384 pp.ISBN: 978-1-4398-0624-1, $89.95 / £57.99Also available as an eBook






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