Applied Statistics Using SPSS, STATISTICA, MATLAB and R

1. Front Matter

   Pages I-XXIV

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2. Introduction

   • Joaquim P. Marques de Sá

   Pages 1-28

3. Presenting and Summarising the Data

   • Joaquim P. Marques de Sá

   Pages 29-80

4. Estimating Data Parameters

   • Joaquim P. Marques de Sá

   Pages 81-109

5. Parametric Tests of Hypotheses

   • Joaquim P. Marques de Sá

   Pages 111-169

6. Non-Parametric Tests of Hypotheses

   • Joaquim P. Marques de Sá

   Pages 171-222

7. Statistical Classification

   • Joaquim P. Marques de Sá

   Pages 223-270

8. Data Regression

   • Joaquim P. Marques de Sá

   Pages 271-328

9. Data Structure Analysis

   • Joaquim P. Marques de Sá

   Pages 329-352

10. Survival Analysis

    • Joaquim P. Marques de Sá

    Pages 353-374

11. Directional Data

    • Joaquim P. Marques de Sá

    Pages 375-401

12. Back Matter

    Pages 403-505

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Four years have passed since the first edition of this book. During this time I have had the opportunity to apply it in classes obtaining feedback from students and inspiration for improvements. I have also benefited from many comments by users of the book. For the present second edition large parts of the book have undergone major revision, although the basic concept – concise but sufficiently rigorous mathematical treatment with emphasis on computer applications to real datasets –, has been retained. The second edition improvements are as follows: • Inclusion of R as an application tool. As a matter of fact, R is a free software product which has nowadays reached a high level of maturity and is being increasingly used by many people as a statistical analysis tool. • Chapter 3 has an added section on bootstrap estimation methods, which have gained a large popularity in practical applications. • A revised explanation and treatment of tree classifiers in Chapter 6 with the inclusion of the QUEST approach. • Several improvements of Chapter 7 (regression), namely: details concerning the meaning and computation of multiple and partial correlation coefficients, with examples; a more thorough treatment and exemplification of the ridge regression topic; more attention dedicated to model evaluation. • Inclusion in the book CD of additional MATLAB functions as well as a set of R functions. • Extra examples and exercises have been added in several chapters. • The bibliography has been revised and new references added.

• Applied Statistics
• Classification and Regression
• Data Description
• Directional Statistics
• Factor analysis
• MATLAB
• Probability theory
• Regression
• SPSS
• STATISTICA
• Survival analysis
• calculus
• classification
• statistical analysis
• statistics
• complexity

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) 

• Fac. Engenharia, Universidade do Porto, Porto, Portugal

  Joaquim P. Marques de Sá

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