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This wide-ranging; jargon-free dictionary contains over 2;300 entries on all aspects of statistics; including terms used in computing; mathematics; and probability. It also includes biographical information on over 200 key figures in the field and coverag
* A self-contained introduction to probability; exchangeability and Bayes' rule provides a theoretical understanding of the applied material. * Numerous examples with R-code that can be run ''as-is'' allow the reader to perform the data analyses themselve
This textbook is an introduction to probability theory using measure theory. It is designed for graduate students in a variety of fields (mathematics; statistics; economics; management; finance; computer science; and engineering) who require a working...
Once again; bestselling author and award-winning teacher Andy Field hasn't just broken the traditional textbook mould with his new novel/textbook; he has forged the only statistics book on the market with a terrifying probability bridge; zombies and a...
The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis of longitudinal data; it covers both the underlying statistical theory of each method; and its application to a range
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning; an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing
This bestselling introduction to regression is known for its readability and clarity. Applied Regression; Second Edition organises the material logically and in a way that students find easy to follow. It provides the reader with applied examples; and...
Combining a modern; data-analytic perspective with a focus on applications in the social sciences; the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis; generalized linear models;
Suitable for use by departments ranging from statistics and Engineering to Psychology and Education when the objective of the course is to learn to use the SAS programming language to perform statistical analysis. As the SAS(c) programming language contin
This book describes how generalised linear modelling procedures can be used in many different fields; without becoming entangled in problems of statistical inference. The author shows the unity of many of the commonly used models and provides readers...