probability and random processes

2
Book Reviews 1183 tion of model parameters under the assumption that the sampling distribution is Gaussian, followed by work on linear model fitting and then parameter estimation, under the assumption that the param- eter posterior distribution is approximately multi- variate Gaussian. Chapter 12 looks at the Markov chain Monte Carlo method for estimating poster- ior distributions for high dimensional models invol- ving the evaluation of multidimensional integrals. Bayes factors and their use in model comparison are also discussed. Several examples from physics and astronomy illustrate the power of Bayesian infer- ence in Chapter 13. Chapter 14, on Bayesian infer- ence with Poisson sampling, discusses the use of Bayes’s theorem to compute the posterior distribu- tion of the Poisson process event rate, given the data and prior information. There are five appendices on singular value decomposition, discrete Fourier transforms, derivation of the multivariate Gaussian distribution from the maximum entropy principle and some technical computations. Most chapters end with a summary and problems complement- ing the material, with many worked examples and illustrations in Mathematica ® . The book ends with references and an index. Though the book is aimed at physical science students, all researchers and scientists who are inter- ested in the Bayesian scientific paradigm can bene- fit greatly from the examples and illustrations here. It is a welcome addition to the vast literature on Bayesian inference. Reference Jaynes, E. T. (2003) Probability Theory—the Logic of Science (ed. G. L. Bretthorst). Cambridge: Cam- bridge University Press. Sreenivasan Ravi University of Mysore Manasagangotri SPSS 14 Made Simple P. R. Kinnear and C. D. Gray, 2006 Hove, Psychology Press 569 pp., £15.95 ISBN 978-1-841-69651-5 The principal goal of this book is to provide guid- ance on both running data analysis and the choice of appropriate statistical techniques by using SPSS statistical software. It is an improved and revised version of an earlier edition and is likely to be an appropriate addition to the library of researchers and students conducting research and creating re- ports by using SPSS. It could be valuable to students and researchers, especially in the fields of marketing and psychology. The authors note that the book is designed for individuals with no prior exposure to SPSS, but many of its elements build the SPSS solution to sta- tistical applications from the ground up. Therefore, the book assumes that the reader is already quite familiar with statistics. It consists of 15 chapters with the major topics graphs and charts, compar- ing averages, analysis of variance, between-subjects factorial experiments, within-subjects experiments, mixed factorial experiments, measuring statistical association, regression, multiway frequency anal- ysis, discriminant analysis and logistic regression, and latent variables. Though one could argue the order of the topics, it offers a sufficiently compre- hensive introduction to the uses of SPSS 14. The material for each specific statistical analysis con- sists of an outline description followed by sample SPSS output for illustrating data requirements and interpreting results. This book gives the reader the benefits of screen snapshots of SPSS dialogue boxes and outputs, a comprehensive index and a separate end-of-text glossary. In summary, this is a clearly written guide to ap- plied statistical analysis by using SPSS software. It is filled with examples and exercises that help readers to understand the types of problem that the tech- niques can address. If you are an SPSS enthusiast, a beginner or not, you will find this new edition a satisfying source of valuable information. However, the omission of the use of advanced statistical topics limits its usefulness for advanced researchers. Güldem Gökçek New York University Probability and Random Processes V. Krishnan, 2006 New York, Wiley Interscience xiv + 724 pp., £72.50 ISBN 0-471-70354-0 This book is addressed to communication engineers, queuing theory specialists, signal processing engi- neers, biomedical engineers, physicists and students in these areas. The choice of topics has been moti- vated by the main goal of the author, namely to write one book as a survival guide in probability and random processes. The following list of key topics describes well the contents of the book: random variables; fre- quently used discrete and continuous distributions; moments, transformations and convergence of random sequences; characteristic, generating and moment-generating functions; computer generation of random variates; estimation theory and the asso- ciated orthogonality principle; linear vector spaces,

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Page 1: Probability and Random Processes

Book Reviews 1183

tion of model parameters under the assumption thatthe sampling distribution is Gaussian, followed bywork on linear model fitting and then parameterestimation, under the assumption that the param-eter posterior distribution is approximately multi-variate Gaussian. Chapter 12 looks at the Markovchain Monte Carlo method for estimating poster-ior distributions for high dimensional models invol-ving the evaluation of multidimensional integrals.Bayes factors and their use in model comparison arealso discussed. Several examples from physics andastronomy illustrate the power of Bayesian infer-ence in Chapter 13. Chapter 14, on Bayesian infer-ence with Poisson sampling, discusses the use ofBayes’s theorem to compute the posterior distribu-tion of the Poisson process event rate, given the dataand prior information. There are five appendiceson singular value decomposition, discrete Fouriertransforms, derivation of the multivariate Gaussiandistribution from the maximum entropy principleand some technical computations. Most chaptersend with a summary and problems complement-ing the material, with many worked examples andillustrations in Mathematica®. The book ends withreferences and an index.

Though the book is aimed at physical sciencestudents, all researchers and scientists who are inter-ested in the Bayesian scientific paradigm can bene-fit greatly from the examples and illustrations here.It is a welcome addition to the vast literature onBayesian inference.

ReferenceJaynes, E. T. (2003) Probability Theory—the Logic of

Science (ed. G. L. Bretthorst). Cambridge: Cam-bridge University Press.

Sreenivasan RaviUniversity of Mysore

Manasagangotri

SPSS 14 Made SimpleP. R. Kinnear and C. D. Gray, 2006Hove, Psychology Press569 pp., £15.95ISBN 978-1-841-69651-5

The principal goal of this book is to provide guid-ance on both running data analysis and the choiceof appropriate statistical techniques by using SPSSstatistical software. It is an improved and revisedversion of an earlier edition and is likely to be anappropriate addition to the library of researchersand students conducting research and creating re-ports by using SPSS. It could be valuable to studentsand researchers, especially in the fields of marketingand psychology.

The authors note that the book is designed forindividuals with no prior exposure to SPSS, butmany of its elements build the SPSS solution to sta-tistical applications from the ground up. Therefore,the book assumes that the reader is already quitefamiliar with statistics. It consists of 15 chapterswith the major topics graphs and charts, compar-ing averages, analysis of variance, between-subjectsfactorial experiments, within-subjects experiments,mixed factorial experiments, measuring statisticalassociation, regression, multiway frequency anal-ysis, discriminant analysis and logistic regression,and latent variables. Though one could argue theorder of the topics, it offers a sufficiently compre-hensive introduction to the uses of SPSS 14. Thematerial for each specific statistical analysis con-sists of an outline description followed by sampleSPSS output for illustrating data requirements andinterpreting results. This book gives the reader thebenefits of screen snapshots of SPSS dialogue boxesand outputs, a comprehensive index and a separateend-of-text glossary.

In summary, this is a clearly written guide to ap-plied statistical analysis by using SPSS software. It isfilled with examples and exercises that help readersto understand the types of problem that the tech-niques can address. If you are an SPSS enthusiast,a beginner or not, you will find this new edition asatisfying source of valuable information. However,the omission of the use of advanced statistical topicslimits its usefulness for advanced researchers.

Güldem GökçekNew York University

Probability and Random ProcessesV. Krishnan, 2006New York, Wiley Intersciencexiv + 724 pp., £72.50ISBN 0-471-70354-0

This book is addressed to communication engineers,queuing theory specialists, signal processing engi-neers, biomedical engineers, physicists and studentsin these areas. The choice of topics has been moti-vated by the main goal of the author, namely towrite one book as a survival guide in probabilityand random processes.

The following list of key topics describes wellthe contents of the book: random variables; fre-quently used discrete and continuous distributions;moments, transformations and convergence ofrandom sequences; characteristic, generating andmoment-generatingfunctions;computergenerationof random variates; estimation theory and the asso-ciated orthogonality principle; linear vector spaces,

Page 2: Probability and Random Processes

1184 Book Reviews

matrices, vector and matrix differentiation; vectorrandom variables; random processes and stationa-rity concepts; classification of random processes;random processes through linear systems; Wienerand Kalman filters; application of probability insingle-photon emission tomography.

The material is distributed in chapters and sec-tions. All notions are given by their definitions fol-lowed by basic properties, rules and facts. It isinstructive to see detailed proofs in most of the cases.Therearemorethan300examples,mostofthempro-vided with solutions and comments well illustratingthetheoreticalresults.Manyoftheexamplesaresub-stantiated with graphs that are drawn to scale.

There are small omissions in some places in thetext. For example, when writing about expectation,variance,etc.,theauthorhasnotmentionedtheusualassumption that all these quantities must exist. Also,one must indicate explicitly the range of the argu-ment when dealing with moment-generating func-tions.

Combined with other similar sources, this bookcan be used for undergraduate and graduate univer-sity courses.

Jordan StoyanovNewcastle University

Starter Packs: a Strategy to Fight Hunger inDeveloping Countries?S. Levy (ed.), 2005Reading, CABI Publishing320 pp., £55ISBN 0-851-99008-8

Starterpacksare freehand-outsof seedandfertilizergiven to food insecure households. This book goessome way to bridge the gap between research andpolicy with an assessment of the starter pack policybetween 1999 and 2003 in Malawi.

The text is of use to policy makers wishing tounderstand the Malawi-specific food programme, aswell as those looking to adopt a similar programmein another developing country. The compact disc(CD) in combination with the text will be particu-larly useful for researchers and statisticians who areconcerned with devising and interpreting resultsfrom large scale participatory studies, censuses andhousehold surveys within the constraints of a devel-oping country.

The book is split into five main sections: the ‘Ori-gins and management of starter pack’; the ‘Method-ology of the evaluation programme’; ‘Lessons fromstarter pack’; ‘By special invitation’ (external au-thors commenting on the effect of starter packson the wider issues of food security and development

as a whole, e.g. the effect of acquired immune defi-ciencysyndromeontheworkingadultswhoaremostlikely to obtain a family’s food endowment); andfinally a CD containing the original data for use inSPSS and further details and reports on the logistics,methodology and evaluation process. Although thebook is written from the perspective of policy mak-ers, who are, in the short term, in favour of food aidprogrammes in developing countries, the reader isnevertheless given a thorough introduction to thelogistical, political, economic, evaluation and sus-tainability issues associated with starter packs andtarget inputs programmes in the context of theirbenefits, disadvantages and wider implications.

A modular approach was taken for the research,with each module having different designs to matchthe various objectives. For example, module 5 in the1999–2000studywastitled ‘Measuringthesizeof therural population in Malawi’. Participatory tools andstatistical methods were used to determine the num-ber of people living in individual households andultimately to challenge the 1998 rural populationcensus figures. Other statistical issues included howtodefinefoodinsecurityandthentoestimatethepro-portion of food insecure households, as well as themoral issues of whether to approach the distributionof starter packs at the individual, family or villagelevel, accounting for the logistical problems withexclusion and inclusion errors.

The text is well structured, accessible and sensi-tively written. The CD is easy to move around toobtain details on reports, appendices and raw data.Overall, the text and CD combination would be aninvaluable aid to any policy makers and research-ers looking to introduce a food security programmewithin a developing country. In addition, the textcould be a useful resource for students within statis-tics, economics, politics or development studies, aswell as being of general use to the lay reader with aninterest in measures to overcome food insecurity indeveloping countries.

Emma ReedLondon

Uncertain Judgements—Eliciting Experts’ProbabilitiesA. O. Hagan, C. E. Buck, A. Daneshkhah,J. R. Eiser, P. Garthwaite, D. Jenkinson,J. Oakley and T. Rakow, 2006Chichester, Wileyxiv +322 pp., £37.50ISBN 978-0-470-02999-4

This book is the result of significant effort from arange of professionals with diverse areas of expertise