Gholamreza Hesamian

Gebundenes Buch

Fuzzy Statistical Inferences Based on Fuzzy Random Variables

Beschreibung

This book presents the most commonly used techniques for the most statistical inferences based on fuzzy data. It brings together many of the main ideas used in statistical inferences in one place, based on fuzzy information including fuzzy data. This book covers a much wider range of topics than a typical introductory text on fuzzy statistics. It includes common topics like elementary probability, descriptive statistics, hypothesis tests, one-way ANOVA, control-charts, reliability systems and regression models. The reader is assumed to know calculus and a little fuzzy set theory. The conventional knowledge of probability and statistics is required.

Key Features:
Includes example in Mathematica and MATLAB.Contains theoretical and applied exercises for each section.Presents various popular methods for analyzing fuzzy data.
The book is suitable for students and researchers in statistics, social science, engineering, and economics, and it can be used at graduate and P.h.D level.

Autor

Gholamreza Hesamian is associate professor of Statistics at Payame Noor University, Iran. His research areas include decision theory, probability theory, fuzzy mathematics and statistics.

Produktdetails

• Verlag: Chapman and Hall/CRC / Taylor & Francis
• Seitenzahl: 314
• Erscheinungstermin: 25. Februar 2022
• Englisch
• Abmessung: 240mm x 161mm x 21mm
• Gewicht: 562g
• ISBN-13: 9781032162225
• ISBN-10: 1032162228
• Artikelnr.: 62569728

Rezensionen

"This book presents the most commonly used techniques for the most statistical inferences based on fuzzy data. It brings together many of the main ideas used in statistical inferences in one place, based on fuzzy information including fuzzy data. This book covers a much wider range of topics than a typical introductory text of fuzzy statistics. It includes common topics like elementary probability, descriptive statistics, hypothesis tests, one-way ANOVA, control-charts, reliability systems and regression models. The reader is assumed to know calculus and a little fuzzy set theory. The conventional knowledge of probability and statistics is required." - MathSciNet