Springer Probability Distributions: With Truncated, Log and Bivariate Extensions

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.   Review “The book is clearly written, and makes it easy to read and comprehend the various issues related to probability distributions.” (Sada Nand Dwivedi, ISCB News, iscb.info, Issue 66, December, 2018) “The book gives a concise and practical overview of the commonly used distributions and statistical methods not presented in other publications. Table values and examples are provided as well. … The book is free of theorems. It is intended for anyone who pursues statistical and probability analysis.” (Oleg K. Zakusilo, zbMATH 1396.60003, 2018) From the Back Cover 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. Nick T. Thomopoulos, Ph.D., has degrees in business (B.S.) and in mathematics (M.A.) from the University of Illinois, and in industrial engineering (Ph.D.) from Illinois Institute of Technology (Illinois Tech). He was supervisor of operations research at International Harvester; senior scientist at the IIT Research Institute; and Professor in Industrial Engineering and in the Stuart School of Business at Illinois Tech. He is the author of eleven books including  Fundamentals of Queuing Systems (Springer),  Essentials of Monte Carlo Simulation (Springer),  Applied Forecasting Methods (Prentice Hall), and  Fundamentals of Production, Inventory and the Supply Chain (Atlantic). He has published many papers and has consulted in a wide variety of industries in the United States, Europe and Asia. Dr. Thomopoulos has received honors over the years, such as the Rist Prize from the Military Operations Research Society for new developments in queuing theory; the Distinguished Professor Award in Bangkok, Thailand from the Illinois Tech Asian