
Fuzzy Statistics
James J. Buckley(Author)
Springer (Publisher)
Published on 5. April 2004
Book
Hardback
XI, 168 pages
978-3-540-21084-9 (ISBN)
Description
1. 1 Introduction This book is written in four major divisions. The first part is the introductory chapters consisting of Chapters 1 and 2. In part two, Chapters 3-11, we develop fuzzy estimation. For example, in Chapter 3 we construct a fuzzy estimator for the mean of a normal distribution assuming the variance is known. More details on fuzzy estimation are in Chapter 3 and then after Chapter 3, Chapters 4-11 can be read independently. Part three, Chapters 12- 20, are on fuzzy hypothesis testing. For example, in Chapter 12 we consider the test Ho : /1 = /10 verses HI : /1 f=- /10 where /1 is the mean of a normal distribution with known variance, but we use a fuzzy number (from Chapter 3) estimator of /1 in the test statistic. More details on fuzzy hypothesis testing are in Chapter 12 and then after Chapter 12 Chapters 13-20 may be read independently. Part four, Chapters 21-27, are on fuzzy regression and fuzzy prediction. We start with fuzzy correlation in Chapter 21. Simple linear regression is the topic in Chapters 22-24 and Chapters 25-27 concentrate on multiple linear regression. Part two (fuzzy estimation) is used in Chapters 22 and 25; and part 3 (fuzzy hypothesis testing) is employed in Chapters 24 and 27. Fuzzy prediction is contained in Chapters 23 and 26. A most important part of our models in fuzzy statistics is that we always start with a random sample producing crisp (non-fuzzy) data.
More details
Series
Edition
2004 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
XI, 168 p.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 15 mm
Weight
442 gr
ISBN-13
978-3-540-21084-9 (9783540210849)
DOI
10.1007/978-3-540-39919-3
Schweitzer Classification
Other editions
Additional editions


Content
Fuzzy Sets.- Estimate ?, Variance Known.- Estimate ?, Variance Unknown.- Estimate p, Binomial Population.- Estimate ?2 from a Normal Population.- Estimate µ 1 - µ 2, Variances Known.- Estimate ? 1 - ? 2, Variances Unknown.- Estimate d =? 1 - ? 2, Matched Pairs.- Estimate p 1 - p 2, Binomial Populations.- Estimate ? 1 2 /? 2 2 , Normal Populations.- Tests on µ, Variance Known.- Tests on µ, Variance Unknown.- Tests on p for a Binomial Population.- Tests on ? 2, Normal Population.- Tests ? 1 verses ? 2, Variances Known.- Test ? 1 verses ? 2, Variances Unknown.- Test p 1 = p 2, Binomial Populations.- Test d = µ 1 - µ 2 , Matched Pairs.- Test ? 1 2 verses ? 2 2 , Normal Populations.- Fuzzy Correlation.- Estimation in Simple Linear Regression.- Fuzzy Prediction in Linear Regression.- Hypothesis Testing in Regression.- Estimation in Multiple Regression.- Fuzzy Prediction in Regression.- Hypothesis Testing in Regression.- Summary and Questions.- Maple Commands.