[R] New Book: Statistical Psychology with R [in French]
spencer.graves at structuremonitoring.com
Wed Jan 23 11:47:54 CET 2013
Dear M. Noel:
You may know that there is a list of books on the R web site
(www.r-project.org -> "books": www.r-project.org/doc/bib/R-books.html).
I'm not sure what you should do to get this book listed there. If no
one else suggests what to do, you might wish to write to Frau Palege in
the Institut für Statistik und Mathematik, Wirtschaftsuniversität Wien,
evelyn.palige at wu.ac.at. If she does not handle this, she might be able
to find someone who does.
On 1/22/2013 11:56 PM, Yvonnick Noel wrote:
> Dear useRs,
> French reading people among you might be interested by the following
> Noel, Y. (2013). Psychologie statistique avec R [Statistical
> psychology with R, in French], coll. PratiqueR, Paris: Springer.
> This book provides a detailed presentation of all basics of
> statistical inference for psychologists, both in a fisherian and a
> bayesian approach. Although many authors have recently advocated for
> the use of bayesian statistics in psychology (Wagenmaker et al., 2010,
> 2011 ; Kruschke, 2010 ; Rouder et al., 2009) statistical manuals for
> psychologists barely mention them. This manual provides a full
> bayesian toolbox for commonly encountered problems in psychology and
> social sciences, for comparing proportions, variances and means, and
> discusses the advantages. But all foundations of the frequentist
> approach are also provided, from data description to probability and
> density, through combinatorics and set algebra.
> A special emphasis has been put on the analysis of categorical data
> and contingency tables. Binomial and multinomial models with beta and
> Dirichlet priors are presented, and their use for making (between rows
> or between cells) contrasts in contingency tables is detailed on real
> data. An automatic search of the best model for all problem types is
> implemented in the AtelieR package, available on CRAN.
> Bayesian ANOVA is also presented, and illustrated on real data with
> the help of the AtelieR and R2STATS packages (a GUI for GLM and GLMM
> in R). In addition to classical and Bayesian inference on means,
> direct and Bayesian inference on effect size and standardized effects
> are presented.
> I hope you might find this book useful,
> Best regards,
> Yvonnick Noel
> University of Brittany, Rennes
> R-help at r-project.org mailing list
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code.
Spencer Graves, PE, PhD
President and Chief Technology Officer
Structure Inspection and Monitoring, Inc.
751 Emerson Ct.
San José, CA 95126
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