Springer Applied Statistics Using SPSS, STATISTICA, MATLAB and R

Intended for anyone needing to apply statistical analysis to a large variety of science and engineering problems, this book shows how to use SPSS, MATLAB, STATISTICA and R for data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. The 2nd edition includes the R language, a new section on bootstrap estimation methods and an improved treatment of tree classifiers, plus additional examples and exercises. Review From the reviews: "Aimed at students, professionals and research workers who need to apply statistical analysis to a large variety of practical problems using SPSS, MATLAB and STATISTICA, this book provides a comprehensive coverage of the main statistical analysis topics … . The relevant notions and methods are explained concisely, illustrated with practical examples using real data, presented with the distinct intention of clarifying sensible practical issues." (T. Postelnicu, Zentralblatt MATH, Vol. 1028, 2004) From the reviews of the second edition: "Readership: Students, professionals and research workers … who are interested in statistical methods and statistical program packages. The book is a … large treatment of many basic statistical methods and procedures. It presents both theoretical issues and a wide variety of applications, examples and exercises. These cover such areas as engineering, medicine, biology, psychology, economy, geology, and astronomy. … After all, I would easily recommend this book for those who are interested in the program packages mentioned in the title." (Kimmo Vehkalahti, International Statistical Review, Vol. 75 (3), 2007)  From the Back Cover This successful textbook is intended for students, professionals and research workers who need to apply statistical analysis to a large variety of practical problems using SPSS, MATLAB, STATISTICA and R. The book provides a comprehensive coverage of the main statistical analysis topics important for practical applications such as data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. The relevant notions and methods are explained concisely, illustrated with practical examples using real data, presented with the distinct intention of clarifying sensible practical issues. The solutions presented in the examples are obtained with one of the software packages in a pedagogical way. It provides guidance on how to use SPSS, MATLAB, STATISTICA and R in statistical analysis applications without having to delve in the manuals. Major improvements of the second edition are the inclusion of the R language as one of the application tools, a new section on bootstrap estimation methods, a revised explanation and treatment of tree classifiers as well as extra examples and exercises.