Affordable, softcover reprint of a classic textbook
Autorentext
Manfred Denker, Penn State University, USA
Klappentext
This textbook integrates traditional statistical data analysis with new computational experimentation capabilities and concepts of algorithmic complexity and chaotic behavior in nonlinear dynamic systems. This was the first advanced text/reference to bring together such a comprehensive variety of tools for the study of random phenomena occurring in engineering and the natural, life, and social sciences.
- Comprehensive and integrated treatment of uncertainty arising in engineering and scientific phenomena - algorithmic complexity, statistical independence, and nonlinear chaotic behavior
- Extensive exercise sets, examples, and Mathematica® computer experiments that reinforce concepts and algorithmic methods
- Thorough presentation of methods of data compression and representation
- Algorithmic approach to model selection and design of experiments
- Large data sets and 13 Mathematica®-based Uncertain Virtual Worlds(TM) programs and code
Inhalt
Preface.- Introduction.- Notation and Abbreviations.- Part I: Descriptive Statistics - Compressing Data.- Why One Needs to Analyze Data.- Data Representation and Compression.- Analytics Representation of Random Experimental Data.- Part II: Modeling Uncertainty.- Algorithmic Complexity and Random Strings.- Statistical Independence and Kolmogorov's Probability Theory.- Chaos in Dynamical Systems: How Uncertainty Arises in Scientific and Engineering Phenomena.- Part III: Model Specification Design of Experiments.- General Principles of Statistical Analysis.- Statistical Inference for Normal Populations.- Analysis of Variance.- Appendix A: Uncertainty Principle in Signal Processing and Quantum Mechanics.- Appendix B: Fuzzy Systems and Logic.- Appendix C: A Critique of Pure Reason.- Appendix D: The Remarkable Bernoulli Family.- Uncertain Virtual Worlds Mathematica Packages.- Appendix F: Tables.- Index.