Probability Distributions

With Truncated, Log and Bivariate Extensions

Nonfiction, Science & Nature, Mathematics, Statistics
Cover of the book Probability Distributions by Nick T. Thomopoulos, Springer International Publishing
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Author: Nick T. Thomopoulos ISBN: 9783319760421
Publisher: Springer International Publishing Publication: April 9, 2018
Imprint: Springer Language: English
Author: Nick T. Thomopoulos
ISBN: 9783319760421
Publisher: Springer International Publishing
Publication: April 9, 2018
Imprint: Springer
Language: English

This volume presents a concise and practical overview of statistical methods and tables not readily available in other publications.  It begins with a review of the commonly used continuous and discrete probability distributions. Several useful distributions that are not so common and less understood are described with examples and applications in full detail: discrete normal, left-partial, right-partial, left-truncated normal, right-truncated normal, lognormal, bivariate normal, and bivariate lognormal. Table values are provided with examples that enable researchers to easily apply the distributions to real applications and sample data. The left- and right-truncated normal distributions offer a wide variety of shapes in contrast to the symmetrically shaped normal distribution, and a newly developed spread ratio enables analysts to determine which of the three distributions best fits a particular set of sample data. The book will be highly useful to anyone who does statistical and probability analysis. This includes scientists, economists, management scientists, market researchers, engineers, mathematicians, and students in many disciplines.

 

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This volume presents a concise and practical overview of statistical methods and tables not readily available in other publications.  It begins with a review of the commonly used continuous and discrete probability distributions. Several useful distributions that are not so common and less understood are described with examples and applications in full detail: discrete normal, left-partial, right-partial, left-truncated normal, right-truncated normal, lognormal, bivariate normal, and bivariate lognormal. Table values are provided with examples that enable researchers to easily apply the distributions to real applications and sample data. The left- and right-truncated normal distributions offer a wide variety of shapes in contrast to the symmetrically shaped normal distribution, and a newly developed spread ratio enables analysts to determine which of the three distributions best fits a particular set of sample data. The book will be highly useful to anyone who does statistical and probability analysis. This includes scientists, economists, management scientists, market researchers, engineers, mathematicians, and students in many disciplines.

 

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