- Paperback: 192 pages
- Publisher: Wiley-Blackwell; 2nd Edition edition (25 Aug 1993)
- Language English
- ISBN-10: 0471559512
- ISBN-13: 978-0471559511
- Product Dimensions: 21.1 x 13.5 x 1.5 cm
- Amazon Bestsellers Rank: 3,971,746 in Books (See Top 100 in Books)
- See Complete Table of Contents
Statistical Distributions
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Review
"Overall, an excellent book for readers interested in qualitative data analysis. Highly recommended. Upper–division undergraduates through professionals." (Choice, 1 October 2011)
"This new edition continues to illustrate the application of statistical methods to research across various disciplines, including medicine, engineering, business/finance, and the social sciences. Thoroughly revised and updated, the authors have refreshed this book to reflect the changes and current trends in statistical distribution theory that have occured since the publication of the previous edition eight years ago . . . key facts and formulas for forty major probability distributions are presented, making the book an ideal introduction to the general theory of statistical distributions as well as a quick reference on its basic principles". (MyCFO, 22 December 2010)
"This new edition continues to illustrate the application of statistical methods to research across various disciplines, including medicine, engineering, business/finance, and the social sciences. Thoroughly revised and updated, the authors have refreshed this book to reflect the changes and current trends in statistical distribution theory that have occured since the publication of the previous edition eight years ago. The introductory chapters introduce the fundamental concepts of the distributions and the relationships between variables. For each distribution that follows, the key formulae, tables and diagrams are presented in a concise, user–friendly format. Key facts and formulas for forty major probability distributions are presented, making the book an ideal introduction to the general theory of statistical distributions as well as a quick reference on its basic principles". (MyCFO, 22 December 2010)
--This text refers to an alternate Paperback edition.Measurement Science & Technology, January 2001
"a large amount of information clearly set out in a concise form"
--This text refers to an alternate
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First Sentence
A probabilistic experiment is some occurrence such as the tossing of coins, rolling dice, or observation of rainfall on a particular day where a complex natural background leads to a chance outcome. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Back Cover
A probabilistic experiment is some occurrence such as the tossing of coins, rolling dice, or observation of rainfall on a particular day where a complex natural background leads to a chance outcome. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Back Cover
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8 reviews
9 of 9 people found the following review helpful
Very helpful
7 Feb 2004
Format:Paperback
No book can possibly cover all distributions - new ones seem to show up in every new problem that arises. This book covers the common ones, maybe all the distributions a student sees in the first stats course or two.
The coverage is quite good for routine, and some non-routine purposes. I find the characteristic functions especially helpful. Each distribution's description of how it arises is also very useful - it's the kind of information that a practitioner needs in order to apply distributions to problems in meaningful ways.
I know that no book can say everything, but a few additions would have improved this book significantly. More discussion of applications would have helped. So would a discussion of general techniques for generating random numbers - inverse distributions, rejection, etc.
The two real weaknesses I found were in the extreme value and the empirical distributions. Extreme values don't stand alone. They often arise in ways dependent on other distributions. An extreme value distribution might describe the results of many experiments that find the largest of N values drawn from distribution P - with different results according to P. These distributions don't have convenient closed forms, but are amenable to some kinds of analysis anyway.
Perhaps the authors do a reasonable job of empirical distributions in the continuous case, but discrete (categorical) cases arise more in my work. Discrete distributions must answer such questions as: given that my sampling may not have found objects of all possible types, how many unknown types are probably still out there? Lots of problems have distributions too complicated for analysis or too poorly understood for book formulas to work, and must be handled empirically. More discussion of empirical techniques would make this a much stronger reference.
Despite its soft spots, this is a very practical reference. I expect it to be a productive member of my technical library.
7 of 7 people found the following review helpful
Great resource for Statisticians and Quantitative analysts.
14 Jun 2000
Format:Paperback
I have been browsing in bookstores for months looking for something just like this. It has very detailed descriptions and explanations of important elements, such as mean, variance, moment-generating functions, etc. I was a bit dismayed by the price, but more than happy with the information it provided.
4 of 4 people found the following review helpful
Want to fit distributions ? This is the book !
26 Feb 2001
Format:Paperback
This is a very good reference for univariate statistical distributions. It provides maximum likelihood and moment estimation formulas for many distributions i'ven't seen anywhere else. That's right that the price is quite high for the number of pages but this information is invaluable for practitioners who need to fit distributions to real data.
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