From the author of 'The Music of the Primes' and 'Finding Moonshine' comes a short, lively book on five mathematical problems that just refuse be solved - and on how many everyday problems can be solved by maths.
"Preface This book is intended to have three roles and to serve three associated audiences: an introductory text on Bayesian inference starting from first principles, a graduate text on effective current approaches to Bayesian modeling and computation in statistics and related fields, and a handbook of Bayesian methods in applied statistics for general users of and researchers in applied statistics. Although introductory in its early sections, the book is definitely not elementary in the sense of a first text in statistics. The mathematics used in our book is basic probability and statistics, elementary calculus, and linear algebra. A review of probability notation is given in Chapter 1 along with a more detailed list of topics assumed to have been studied. The practical orientation of the book means that the reader's previous experience in probability, statistics, and linear algebra should ideally have included strong computational components. To write an introductory text alone would leave many readers with only a taste of the conceptual elements but no guidance for venturing into genuine practical applications, beyond those where Bayesian methods agree essentially with standard non-Bayesian analyses. On the other hand, we feel it would be a mistake to present the advanced methods without first introducing the basic concepts from our data-analytic perspective. Furthermore, due to the nature of applied statistics, a text on current Bayesian methodology would be incomplete without a variety of worked examples drawn from real applications. To avoid cluttering the main narrative, there are bibliographic notes at the end of each chapter and references at the end of the book"--
The R version of Andy Field's hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences.
Encourages development of application and decision making skills for use in managing raw data and real-world projects. This book includes such topics as scattergrams and time series graphs, simple and multiple regressions, time series analysis, and random sampling.
Provides advanced students with a comprehensive introduction to commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher level mathematics. Each technique chapter: discusses tests for assumptions of analysis, presents a small example and describes varieties of analysis.
Statistics is arguably the main means through which maths appears in non-maths courses. De-mystifying the basics for even the most maths-terrified of students, this book will inspire confident and accurate use of statistics for non-maths courses.