Probably Not: Future Prediction Using Probability and Statistical Inference

Author:   Lawrence N. Dworsky (Motorola, Inc.)
Publisher:   John Wiley & Sons Inc
Edition:   2nd edition
ISBN:  

9781119518105


Pages:   352
Publication Date:   20 September 2019
Format:   Paperback
Availability:   Available To Order   Availability explained
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Probably Not: Future Prediction Using Probability and Statistical Inference


Overview

A revised edition that explores random numbers, probability, and statistical inference at an introductory mathematical level Written in an engaging and entertaining manner, the revised and updated second edition of Probably Not continues to offer an informative guide to probability and prediction. The expanded second edition contains problem and solution sets. In addition, the book’s illustrative examples reveal how we are living in a statistical world, what we can expect, what we really know based upon the information at hand and explains when we only think we know something. The author introduces the principles of probability and explains probability distribution functions. The book covers combined and conditional probabilities and contains a new section on Bayes Theorem and Bayesian Statistics, which features some simple examples including the Presecutor’s Paradox, and Bayesian vs. Frequentist thinking about statistics. New to this edition is a chapter on Benford’s Law that explores measuring the compliance and financial fraud detection using Benford’s Law. This book: Contains relevant mathematics and examples that demonstrate how to use the concepts presented Features a new chapter on Benford’s Law that explains why we find Benford’s law upheld in so many, but not all, natural situations Presents updated Life insurance tables Contains updates on the Gantt Chart example that further develops the discussion of random events Offers a companion site featuring solutions to the problem sets within the book Written for mathematics and statistics students and professionals, the updated edition of Probably Not: Future Prediction Using Probability and Statistical Inference, Second Edition combines the mathematics of probability with real-world examples. LAWRENCE N. DWORSKY, PhD, is a retired Vice President of the Technical Staff and Director of Motorola’s Components Research Laboratory in Schaumburg, Illinois, USA. He is the author of Introduction to Numerical Electrostatics Using MATLAB from Wiley.

Full Product Details

Author:   Lawrence N. Dworsky (Motorola, Inc.)
Publisher:   John Wiley & Sons Inc
Imprint:   John Wiley & Sons Inc
Edition:   2nd edition
Dimensions:   Width: 15.00cm , Height: 1.80cm , Length: 22.40cm
Weight:   0.567kg
ISBN:  

9781119518105


ISBN 10:   1119518105
Pages:   352
Publication Date:   20 September 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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Author Information

LAWRENCE N. DWORSKY, PHD, is a retired Vice President of the Technical Staff and Director of Motorola's Components Research Laboratory in Schaumburg, Illinois, USA. He is the author of Introduction to Numerical Electrostatics Using MATLAB® from Wiley.

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