Data Mining with SPSS Modeler: Theory, Exercises and Solutions

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Springer, Jun 6, 2016 - Mathematics - 1059 pages

Introducing the IBM SPSS Modeler, this book guides readers through data mining processes and presents relevant statistical methods. There is a special focus on step-by-step tutorials and well-documented examples that help demystify complex mathematical algorithms and computer programs. The variety of exercises and solutions as well as an accompanying website with data sets and SPSS Modeler streams are particularly valuable. While intended for students, the simplicity of the Modeler makes the book useful for anyone wishing to learn about basic and more advanced data mining, and put this knowledge into practice.

 

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Contents

Introduction
1
Basic Functions of the SPSS Modeler
25
Univariate Statistics
185
Multivariate Statistics
287
Regression Models
346
Factor Analysis
513
Cluster Analysis
587
Classification Models
713
Using R with the Modeler
985
Appendix
1036
Copyright

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About the author (2016)

Prof. Dr. Tilo Wendler studied mathematics, physics and business information technology. In his doctoral thesis he examined determinants of user expectations in using information technology. With much interest he applied complex statistical methods in the banking sector especially in the field of rating methods. He has been teaching business statistics and data mining for ten years.

Dr. Sören Gröttrup studied mathematics and computer science with focus on probability theory and statistics and got his Ph.D. for his research on biological models. Parallel to his doctoral studies, he worked in a research institute as a data analyst on genomic data sets. Today, he works as a data analyst and statistician in the industrial and marketing sector.

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