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The article reviews the book "Metode cantitative în studiul fenomenului religios (Quantitative Methods in the Study of Religious Phenomena)," by Claudiu Herteliu.

The article reviews the book "Super Crunchers: Why Thinking-By-Numbers Is the New Way to Be Smart," by Ian Ayers.

The reviewed book is a large overview of European changes during the 20th century. Chapters are devoted to different fields of social life, from politics to urbanization, and even the arts. The author found his sources mainly in foreign-language literature. Statistics and ample references are given for every subject discussed, according to the reviewer.

The article reviews the book "Statistics in the Law," by Joseph B. Kadane.

The article reviews the book "Encyclopedia of Statistical Sciences," volumes 1-16, edited by Samuel Kotz, N. Balakrishnan, C. B. Read and B. Vidakovic.

The article presents a review of the book "The Mirage of China: Anti-Humanism, Narcissism and Corporeality of the Contemporary World," by Xin Liu.

Charles Wheelan's Naked Statistics: Stripping the Dread from the Data (2013) reintroduces the field of statistics to the apathetic reader in an approachable and sympathetic way. By focusing on the acquisition of appreciation for the field over straightforward comprehension, Wheelan is able to achieve what many qualitative researchers have striven for in reintroducing the field to those thought previously lost. [ABSTRACT FROM AUTHOR]

It is a quick read and provides a nice stats refresher with some humor built in. By Charles Wheelan This book is a favorite of mine because it simplifies statistical concepts through real-world examples. [Extracted from the article]

The article reviews the book "Probability and Statistics by Example. Basic Probability and Statistics," Vol. I. by M. Ya. Kelbert and Yu. M. Sukhov.

The article reviews the book "Karl Pearson: The Scientific Life in a Statistical Age," by Theodore M. Porter.

The article reviews the book "More Damned Lies and Statistics: How Numbers Confuse Public Issues," by Joel Best.

The article reviews the book "Applied Statistics for Public Policy," by Brian P. Macfie and Philip M. Nufrio.

This article reviews the book "Constrained Statistical Inference: Inequality, Order, and Shape Restrictions," by M. J. Silvapulle and P. K. Sen.

This book surveys the main topics in spatial statistics, including modeling random fields, variogram estimation, hierarchical models, and spatial point processes. She runs through the most important topics in spatial statistics, from kriging and variogram fitting to Markov random field modeling to the estimation of log-Gaussian Cox point processes, and boils down each of these complex topics to its core elements and explains them clearly and succinctly. It is clear that an enormous amount of effort went into these worked examples, though as with the theoretical topics, van Lieshout explains everything so clearly and concisely that she makes the applications and R coding look easy, and in some cases almost trivial. [Extracted from the article]

Chapter 8 simplifies the task to the estimation of the central mean subspace, replacing the SDR conditional independence assumption (that Graph HT ht for some matrix ) with an assumption on the conditional mean: Graph HT ht . To this point, the dimension of the SDR subspace has been taken as given, and Chapters 9 and 10 examine techniques for determining the dimension from data. Chapter 11 reexamines estimation of the central mean subspace with the outer product of gradients and minimum average variance estimators. [Extracted from the article]

This book has been written "for people that have to apply statistical methods in their research but whose main interest is not in theorems and proofs" (from the preface). From there on all statistical procedures are exemplified via R commands starting with point estimation in Chapter 2, one and two sample testing problems in Chapter 3 and confidence estimation in Chapter 4. Chapter 11 on Generalised Linear Models and Chapter 12 on Spatial Statistics have no counterpart in Rasch and Schott ([1]), which testifies to the rather recent addition of geostatistics to the range of methods decent statisticians are supposed to know about. [Extracted from the article]

Compositional Data (CoDa) Analysis is a growing field of statistical methodology that finds its way into more and more areas of research. Chapter 1, Compositional Data as a Methodological Concept, introduces the main problems with the analysis of CoDa through examples, as well as a synthesis of the logratio methodology that can be followed to avoid those problems. Chapter 4 is devoted to the visualization of CoDa, while Chapter 5 introduces the first steps to follow in a statistical analysis. [Extracted from the article]

Health technology assessments typically use cost-effectiveness analyses, which deal with comparing health interventions/treatments based on both cost and effectiveness (ability to improve health). According to the preface, the book provides the basis of statistical decision theory and methods required for cost-effectiveness analysis, and is aimed at students of health economics with a solid background in statistics, as well as applied statisticians, researchers in health economics, and health managers. The first utility function compares the net benefit in expectation, while the second utility function uses a comparison for net benefit in probability. [Extracted from the article]

A convex, compact, and possibly discontinuous better reply secure game has a Nash equilibrium. We introduce a very weak notion of continuity that can be used to establish that a game is better reply secure and we show that this notion of continuity is satisfied by a large class of games. [ABSTRACT FROM AUTHOR]

Reviews the book "Statistical Methods for Communication Science," by Andrew F. Hayes.

This is the first edition of Bartolucci, Bacci, and Gnaldi's Statistical Analysis of Questionnaires book and consists of six chapters, which focuses mostly on Item Response Theory (IRT). The sixth and final chapter of the book provides a discussion on some extensions of the traditional IRT model to IRT models with covariates, models for multilevel data, multidimensional IRT models, and IRT models in the structural equation modeling (SEM) framework. The two examples provided in R, using the I MultiLCIRT i package (Bartolucci et al., [1]), are the estimation of a graded response model with covariates using the Russian Longitudinal data and a multilevel and multidimensional (i.e., three dimension) dichotomous IRT model for the Italian education dataset. [Extracted from the article]

He successfully argues for and motivates the use of randomization through a rich collection of stories of successes and failures - and this fact alone makes me want to recommend the book to others. However, I had to wonder - given the lofty goal of the book - is some level of over-stating conclusions actually worth getting more people to buy into the importance of careful design and randomization? My copy of the book has graphite marks on about a quarter of its pages (despite my daughter's admonitions about writing in books)!. [Extracted from the article]

The article reviews several books on data mining and statistical computations including "Data Analysis: An Introduction," by Michael S. Lewis-Beck, "The Design & Analysis of Computer Experiments," by Thomas I. Santer, Brian J. Williams, and William I. Notz, "Statistical Data Mining & Knowledge Discovery," edited by Hamparsum Bozdogan, "Data Mining: Multimedia, Soft Computing, & Bioinformatics," by Shmita Mitra and Tinku Acharya, and "Computational Methods in Statistics and Econometrics," by Hisashi Tanizaki.

For estimating a normal variance under the squared error loss function it is well known that the best affine (location and scale) equivariant estimator, which is better than the maximum likelihood estimator as well as the unbiased estimator, is also inadmissible. The improved estimators, e.g ., stein type, brown type and Brewster–Zidek type, are all scale equivariant but not location invariant. Lately, a good amount of research has been done to compare the improved estimators in terms of risk, but comparatively less attention had been paid to compare these estimators in terms of the Pitman nearness criterion (PNC) as well as the stochastic domination criterion (SDC). In this paper, we have undertaken a comprehensive study to compare various variance estimators in terms of the PNC and the SDC, which has been long overdue. Finally, using the results for risk, the PNC and the SDC, we propose a compromise estimator (sort of a robust estimator) which appears to work ‘well’ under all the criteria discussed above. [ABSTRACT FROM AUTHOR]

Reviews the book "The Statistical Turn in Economics: 1903-1955," by A.J. Jolink and Jan Tinbergen.

Reviews several books on applied statistics. "Design and Analysis of Clinical Trials--Concepts and Methodologies," 2nd ed., by S. -C. Chow and J. -P Liu; "Cogwheels of the Mind: The Story of Venn Diagrams," by A. W. F. Edwards; "Applied Bayesian Modeling and Causal Inference for Incomplete-Data Perspectives," edited by A. Gelman and X. -L. Meng; "Handbook of Beta Distribution and Its Applications," edited by A. K. Gupta and S. Naharajah; "Econometric Methods With Applications in Business and Economics," by C. Heij, P. de Boer, P. H. Franses, T. Kloek, and H. K. van Dijk; Others.

Reviews several books. "Statistics and the Evaluation of Evidence for Forensic Scientists," 2nd ed., by Colin Aitken and Franco Taroni; "Reckoning With Risk," by Gerd Gigerenzer; "Pensions and Insurance Before 1800: A Social History," by C. G. Lewin.

Reviews the book "Statistical Group Comparison," by Tim Futing Liao.

Reviews several books about statistics. "Bioinformatics," by D. R. Westhead, J. H. Parish and R. M. Twyman; "Data Analysis Tools for DNA Microarrays," by S. Draghici; "Pocket Guide to Biotechnology and Genetic Engineering," by R. D. Schmid; "Scan Statistics," by J. Glaz, J. Naus and S. Wallenstein.

A review is presented of the book "Numbers Rule Your World: The Hidden Influence of Probability & Statistics on Everything You Do," by Kaiser Fung.

Reviews the book "Statistical Methods for the Analysis of Repeated Measurements," by Charles S. Davis.

Reviews books in statistics. 'Missing Data,' by Paul D. Allison; 'Statistical Rules of Thumb,' by Gerald van Belle; 'Bayesian Statistical Modelling,' by Peter Congdon.

Reviews the book 'Structural Equation Modeling: Foundations and Extension,' by David Kaplan.

Reviews the non-fiction book 'Applied Multivariate Statistics for the Social Sciences,' 4th ed., by James P. Stevens.

Reviews the non-fiction book 'Generalizability Theory.'

Reviews several books on statistics. 'Probability and Statistical Inference. Sixth Edition,' by R.V. Hogg and E.A. Tanis; 'Generalized, Linear, and Mixed Models,' by C.E.M. Cullo and S.R. Searle; 'A Course in Time Series Analysis,' edited by D. Pena, G.C. Tiao and R.S. Tsay; 'S Programming,' by W.N. Venables and B.D. Ripley.

Reviews the book 'Handbook of Statistics, Volume 19 Stochastic Processes: Theory and Methods,' edited by D.N. Shanbhag and C.R. Rao.

The present book review of Statistics with Confidence is framed in terms of both the recent report of the APA Task Force on Statistical Inference and ongoing movements in the field. The review is structured in terms of two major issues: the interpretation of confidence intervals (null hypothesis significance testing [NHST] versus non-NHST) and the ethics of statistics. [ABSTRACT FROM AUTHOR]

Reviews the book 'Statistics and Neural Networks-- Advances at the Interface,' edited by J.W. Kay and D.M. Titterington.

Reviews the book 'Statistics on the Table: The History of Statistical Concepts and Methods,' by Stephen M. Stigler.

The article reviews the book "The Enlightened Bracketologist: The Final Four of Everything," edited by Mark Reiter and Richard Sandomir.

The article reviews the book "Sources of Unofficial U.K. Statistics" by David Mort and Wendy Wilkins.

Reviews the book "New View Almanac," by Jenny Tesar and illustration by Bob Italiano and David C. Bell.