Introductory Statistics and Random Phenomena: Uncertainty, Complexity and Chaotic Behavior in Engineering and ScienceBirkhäuser, 16 ก.ย. 2017 - 509 หน้า 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 WorldsTM 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
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เนื้อหา
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Part II MODELING UNCERTAINTY | 200 |
Part III MODEL SPECIFICATIONDESIGN OF EXPERIMENTS | 365 |
Appendix A Uncertainty Principle in Signal Processing and Quantum Mechanics | 461 |
Appendix B Fuzzy Systems and Logic | 465 |
Appendix C A Critique of Pure Reason | 468 |
Appendix D The Remarkable Bernoulli Family1 | 473 |
Appendix E Uncertain Virtual Worlds Mathematica Packages | 477 |
Appendix F Tables | 497 |
Index | 503 |
ฉบับอื่นๆ - ดูทั้งหมด
Introductory Statistics and Random Phenomena: Uncertainty, Complexity and ... Manfred Denker,Wojbor Woyczynski ชมบางส่วนของหนังสือ - 1998 |
Introductory Statistics and Random Phenomena: Uncertainty, Complexity and ... Manfred Denker,Wojbor Woyczynski ชมบางส่วนของหนังสือ - 2012 |
คำและวลีที่พบบ่อย
algorithm approximation AspectBatio->1 ball Bibliographical Notes binary strings binomial called Cantor set Central Limit Theorem Chapter components confidence interval consider correlation dimension cumulative d.f. cumulative distribution function data set defined degrees of freedom density discrete dynamical system entropy equations ergodic estimator Example experimental exponential finite formula fractal FX(x Gaussian graph Graphics histogram hypothesis independent random variables integral invariant measure iterations Kolmogorov complexity Large Numbers Law of Large linear ListPlot Martin-Löf test Mathematica Experiment mathematical orbit package parameter plot Pr(X probability distribution probability theory pseudorandom pseudorandom number Q-Q plot quantile function random events Random Phenomena random quantity random sample random vector real numbers regression relative frequency sample mean sample points sample space Section selected sequence significance level simulated Statistics strings of length test function trajectories unit interval values variance