Applied Statistics Using Spss Statistica And Matlab


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Applied Statistics Using SPSS, STATISTICA and MATLAB


Applied Statistics Using SPSS, STATISTICA and MATLAB

Author: Joaquim P. Marques de Sá

language: en

Publisher: Springer Science & Business Media

Release Date: 2013-03-09


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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 text 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, MATALB and STATISTICA in statistical analysis applications without having to delve in the manuals. The accompanying CD-Rom includes several specific software tools for the topics described in the book, including a set of MATLAB functions for directional statistics as well as the data sets used in the examples and exercises covering a broad spectrum of areas from engineering, medicine, biology, psychology, economy, geology, and astronomy.

Applied Statistics


Applied Statistics

Author:

language: en

Publisher:

Release Date: 2007


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Applied Statistics Using SPSS, STATISTICA, MATLAB and R


Applied Statistics Using SPSS, STATISTICA, MATLAB and R

Author: Joaquim P. Marques de Sá

language: en

Publisher: Springer

Release Date: 2009-09-02


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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.