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Birkhäuser

Introductory Statistics and Random Phenomena

Uncertainty, Complexity and Chaotic Behavior in Engineering and Science

  • Textbook
  • © 2017

Overview

  • Affordable, softcover reprint of a classic textbook?
  • Integrates ideas about statistics of random phenomena stemming from algorithmic computational complexity, classical probability theory, and chaotic behavior in nonlinear systems
  • Provides examples of statistical problems that arise in real-life industrial and scientific lab settings

Part of the book series: Modern Birkhäuser Classics (MBC)

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Table of contents (9 chapters)

  1. Descriptive Statistics-Compressing Data

  2. Modeling Uncertainty

  3. Model Specification-Design of Experiments

Keywords

About this book

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.

The crucial computer experiments are conducted using the readily available computer program Mathematica® Uncertain Virtual Worlds™ software packages which optimize and facilitate the simulation environment.  Brief tutorials are included that explain how to use the Mathematica® programs for effective simulation and computer experiments.  Large and original real-life data sets are introduced and analyzed as a model for independent study.


This is an excellent classroom tool and self-study guide.  The material is presented in a clear and accessible style providing numerous exercises and bibliographical notes suggesting further reading.


Topics and Features
  • 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™ programs and code

This text is an excellent resource for all applied statisticians, engineers, and scientists who need to use modern statistical analysis methods to investigate and model their data.  The present, softcover reprint is designed to make this classic textbook available to a wider audience.




Authors and Affiliations

  • Department of Mathematics, Pennsylvania State University, State College, USA

    Manfred Denker

  • Math, Applied Math, & Stat, Yost 229, Case Western Reserve University, Cleveland, USA

    Wojbor Woyczynski

About the authors

Manfred Denker, Penn State University, USA

Wojbor Woyczynski, Case Western Reserve University, USA

Bibliographic Information

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