Continuous Univariate Distributions
Norman L. Johnson
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Description for Continuous Univariate Distributions
Hardcover. This volume contains a detailed description of the statistical distributions that are commonly used in various applied areas, such as engineering, business, economics and the behavioural, biological and environmental sciences. It covers general and specific continuous distributions. Series: Wiley Series in Probability and Statistics. Num Pages: 784 pages, illustrations. BIC Classification: PBT; PBW. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 243 x 167 x 46. Weight in Grams: 1240.
The definitive reference for statistical distributions
Continuous Univariate Distributions, Volume 1 offers comprehensive guidance toward the most commonly used statistical distributions, including normal, lognormal, inverse Gaussian, Pareto, Cauchy, gamma distributions and more. Each distribution includes clear definitions and properties, plus methods of inference, applications, algorithms, characterizations, and reference to other related distributions. Organized for easy navigation and quick reference, this book is an invaluable resource for investors, data analysts, or anyone working with statistical distributions on a regular basis.
Product Details
Format
Hardback
Publication date
1994
Publisher
John Wiley & Sons Inc United States
Number of pages
784
Condition
New
Series
Wiley Series in Probability and Statistics
Number of Pages
784
Place of Publication
, United States
ISBN
9780471584957
SKU
V9780471584957
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50
About Norman L. Johnson
NORMAN L. JOHNSON, PHD, was Professor Emeritus, Department of Statistics, University of North Carolina at Chapel Hill. Dr. Johnson was Editor-in-Chief of the Encyclopedia of Statistical Sciences, Second Edition. SAMUEL KOTZ, PHD, is Professor and Research Scholar, Department of Engineering Management and Systems Engineering, The George Washington University in Washington, DC.
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