With a useful index of notations at the beginning, this book explains and illustrates the theory and application of data analysis methods from univariate to multidimensional and how to learn and use them efficiently. This book is well illustrated and is a useful and well-documented review of the most important data analysis techniques.
- Describes, in detail, exploratory data analysis techniques from the univariate to the multivariate ones
- Features a complete description of correspondence analysis and factor analysis techniques as multidimensional statistical data analysis techniques, illustrated with concrete and understandable examples
- Includes a modern and up-to-date description of clustering algorithms with many properties which gives a new role of clustering in data analysis techniques
Table of Contents
General Presentation. Statistical Data Exploration. 1-D Statistical Data Analysis. 2-D Statistical Data Analysis. N-D Statistical Data Analysis. Factor Analysis of Individuals-Variables Data Sets. Principal Components Analysis. 2-D Correspondence Analysis. N-D Correspondence Analysis. Classification of Individuals-Variables Data Sets. Classification and Analysis of Proximities Data Sets. Computer Aspects of Advanced Exploratory Data Analysis. Appendix 1: List of Notations. Appendix 2: Reference Data Sets. References. Author Index. Subject Index. Data Analysis News.