Probably Not -  Lawrence N. Dworsky

Probably Not (eBook)

Future Prediction Using Probability and Statistical Inference
eBook Download: PDF
2019 | 1. Auflage
352 Seiten
Wiley (Verlag)
978-1-119-51813-6 (ISBN)
Systemvoraussetzungen
83,99 inkl. MwSt
  • Download sofort lieferbar
  • Zahlungsarten anzeigen

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.



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.


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.
Erscheint lt. Verlag 26.7.2019
Sprache englisch
Themenwelt Mathematik / Informatik Mathematik Statistik
ISBN-10 1-119-51813-X / 111951813X
ISBN-13 978-1-119-51813-6 / 9781119518136
Haben Sie eine Frage zum Produkt?
PDFPDF (Adobe DRM)
Größe: 4,8 MB

Kopierschutz: Adobe-DRM
Adobe-DRM ist ein Kopierschutz, der das eBook vor Mißbrauch schützen soll. Dabei wird das eBook bereits beim Download auf Ihre persönliche Adobe-ID autorisiert. Lesen können Sie das eBook dann nur auf den Geräten, welche ebenfalls auf Ihre Adobe-ID registriert sind.
Details zum Adobe-DRM

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen eine Adobe-ID und die Software Adobe Digital Editions (kostenlos). Von der Benutzung der OverDrive Media Console raten wir Ihnen ab. Erfahrungsgemäß treten hier gehäuft Probleme mit dem Adobe DRM auf.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen eine Adobe-ID sowie eine kostenlose App.
Geräteliste und zusätzliche Hinweise

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich