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Serious Stats: A guide to advanced statistics for the behavioral sciences [Paperback]

Thomas Baguley

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Book Description

25 Jun 2012 0230577180 978-0230577183
Ideal for experienced students and researchers in the social sciences who wish to refresh or extend their understanding of statistics, and to apply advanced statistical procedures using SPSS or R. Key theory is reviewed and illustrated with examples of how to apply these concepts using real data.

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"This is an excellent text on advanced univariate statistics covering the range from probability distributions to multilevel models. The book is perfect for advanced undergraduates, honours students, and beginning graduate students." - Toon Cillessen, Professor of Psychology at Radboud University, Nijmegen, The Netherlands

"Serious Stats is a tour de force and a highly accessible exception amongst statistics textbooks. Blow the dust and presumptions off your undergraduate statistics and learn about the things you really need to know about modelling data and how to achieve them, especially if you're R-curious. Baguley will become the must-have resource for researchers who are serious about getting the most from their experiments." - Philip J. Benson, Senior Lecturer, School of Psychology, University of Aberdeen, UK

"A good resource for those wishing to build a fundamental understanding of probability and statistics and their applications to complex scientific data." - Adam Moore, The Center for Advanced Brain Imaging, Georgia Institute of Technology, USA

"A nice and almost encyclopaedic companion for behavioural scientists, which covers not only the usual topics of ANOVA and regression, but also such important themes like effect size and power, resampling methods, Bayesian inference, discrete outcomes, and multilevel models, with many useful references for further reading." - Gerard van Breukelen, Associate Professor of Statistics, Maastricht University, The Netherlands

"This book gives one of the most comprehensive, detailed and, importantly, readable accounts of statistical methods used in behavioural research. It provides superb coverage of the principles and assumptions of standard methods of analysis, as well as of the more complex and powerful techniques available in the statistical armoury, such as multilevel modelling. It is a book which every Experimental Psychologist will find helpful to have on their shelf." - Michael Pilling, Lecturer in Psychology, Oxford Brookes University, UK




Book Description

Bridges the gap between the undergraduate and postgraduate levels, providing readers with a refresher of the skills they have learnt andthen progressing to more advanced statistical methods

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Front Cover | Copyright | Table of Contents | Excerpt | Index
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2 of 2 people found the following review helpful
5.0 out of 5 stars Serious Stats- A guide to statistics in the behavioral sciences .. Misnamed? 6 Feb 2014
By James Brownlow - Published on Amazon.com
Format:Paperback|Verified Purchase
Better- "A comprehensive guide to statistics for the behavorial scientist"

This book is an 800 page tour de force of statistical methods. The good news is that the author is a psychologist so the presentation of key conceps and examples are well written. The bad news is that the author is a psychologist (and the book is already 800+ pages) so presentations are short and to the point. I had a problem at work that involved proportional odds logistic regression, and indeed, an example is given. One example. Proportional odds using logistic regression. Are there other methods? Yes, but these are not discussed. Does the example show / interpret odds ratios? No.... confidence intervals for the coefficients? Yes, Wald method, Confidence intervals for odds ratios? No.. Discussion of the ever (de)pressing issue "when can categorical data be analyzed as though it were from an interval scale" meticulously avoided.

Bayesian methods are presented; no mention of current trends in Markov Chain Monte Carlo estimation. Bayesian discussion is limited to analyses that have tractable (prior * likelihood) functions. Current applications of Bayesian techniques are more along the lines of "please step away from the conjugate prior," but the concepts are clear. Bayes factors are presented as well as likelihood estimation, and use of the AIC, BIC.

In fairness, the book covers so many topics that no one topic can get much depth. The book also addresses effect size, confidence and power of a test- all important aspects of inference. Also kudos to the author for providing code snippets in R. R ubiquitous and (free) so this a welcome aspect ot the book. I recommend the book to anyone looking to use statistical methods in the behavorial (and other) sciences. One would benefit from consultation with a statistician having once expored the book for the various means and methods for analysis and design of an experiment.
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