Applied Statistics Using SPSS, STATISTICA, MATLAB and R

This book provides broad coverage of statistical topics and methods, and goes further to include applications of real-life data and problems across a range of fields. An instructional guide is included showing how to use STATISTICA, SPSS and MATLAB in statistical analysis applications. The book includes the popular free R language as one of the application tools. This new Second Edition includes a section on bootstrap estimation methods, which have earned considerable popularity in practical applications It also expands the section on correlation measures, adding matters such as partial and multiple correlation.

Wide coverage of Statistical topics and methods Application to real life data and problems in various fields Guidance on how to use STATISTICA, SPSS, MATLAB and R in statistical analysis applications

Klappentext

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.

Inhalt
Presenting and Summarising the Data.- Estimating Data Parameters.- Parametric Tests of Hypotheses.- Non-Parametric Tests of Hypotheses.- Statistical Classification.- Data Regression.- Data Structure Analysis.- Survival Analysis.- Directional Data.