Statistical Distributions

Applications and Parameter Estimates

Nonfiction, Science & Nature, Mathematics, Statistics
Cover of the book Statistical Distributions by Nick T. Thomopoulos, Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Nick T. Thomopoulos ISBN: 9783319651125
Publisher: Springer International Publishing Publication: October 10, 2017
Imprint: Springer Language: English
Author: Nick T. Thomopoulos
ISBN: 9783319651125
Publisher: Springer International Publishing
Publication: October 10, 2017
Imprint: Springer
Language: English

This book gives a description of the group of statistical distributions that have ample application to studies in statistics and probability. Understanding statistical distributions is fundamental for researchers in almost all disciplines.  The informed researcher will select the statistical distribution that best fits the data in the study at hand.   Some of the distributions are well known to the general researcher and are in use in a wide variety of ways.  Other useful distributions are less understood and are not in common use.  The book describes when and how to apply each of the distributions in research studies, with a goal to identify the distribution that best applies to the study.  The distributions are for continuous, discrete, and bivariate random variables.  In most studies, the parameter values are not known a priori, and sample data is needed to estimate parameter values.  In other scenarios, no sample data is available, and the researcher seeks some insight that allows the estimate of the parameter values to be gained.

This handbook of statistical distributions provides a working knowledge of applying common and uncommon statistical distributions in research studies.  These nineteen distributions are: continuous uniform, exponential, Erlang, gamma, beta, Weibull, normal, lognormal, left-truncated normal, right-truncated normal, triangular, discrete uniform, binomial, geometric, Pascal, Poisson, hyper-geometric, bivariate normal, and bivariate lognormal.  Some are from continuous data and others are from discrete and bivariate data.  This group of statistical distributions has ample application to studies in statistics and probability and practical use in real situations.  Additionally, this book explains computing the cumulative probability of each distribution and estimating the parameter values either with sample data or without sample data.  Examples are provided throughout to guide the reader.

Accuracy in choosing and applying statistical distributions is particularly imperative for anyone who does statistical and probability analysis, including management scientists, market researchers, engineers, mathematicians, physicists, chemists, economists, social science researchers, and students in many disciplines.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book gives a description of the group of statistical distributions that have ample application to studies in statistics and probability. Understanding statistical distributions is fundamental for researchers in almost all disciplines.  The informed researcher will select the statistical distribution that best fits the data in the study at hand.   Some of the distributions are well known to the general researcher and are in use in a wide variety of ways.  Other useful distributions are less understood and are not in common use.  The book describes when and how to apply each of the distributions in research studies, with a goal to identify the distribution that best applies to the study.  The distributions are for continuous, discrete, and bivariate random variables.  In most studies, the parameter values are not known a priori, and sample data is needed to estimate parameter values.  In other scenarios, no sample data is available, and the researcher seeks some insight that allows the estimate of the parameter values to be gained.

This handbook of statistical distributions provides a working knowledge of applying common and uncommon statistical distributions in research studies.  These nineteen distributions are: continuous uniform, exponential, Erlang, gamma, beta, Weibull, normal, lognormal, left-truncated normal, right-truncated normal, triangular, discrete uniform, binomial, geometric, Pascal, Poisson, hyper-geometric, bivariate normal, and bivariate lognormal.  Some are from continuous data and others are from discrete and bivariate data.  This group of statistical distributions has ample application to studies in statistics and probability and practical use in real situations.  Additionally, this book explains computing the cumulative probability of each distribution and estimating the parameter values either with sample data or without sample data.  Examples are provided throughout to guide the reader.

Accuracy in choosing and applying statistical distributions is particularly imperative for anyone who does statistical and probability analysis, including management scientists, market researchers, engineers, mathematicians, physicists, chemists, economists, social science researchers, and students in many disciplines.

More books from Springer International Publishing

Cover of the book Fuzzy Logic and Applications by Nick T. Thomopoulos
Cover of the book Microbial Styrene Degradation by Nick T. Thomopoulos
Cover of the book The DARPA Robotics Challenge Finals: Humanoid Robots To The Rescue by Nick T. Thomopoulos
Cover of the book Evolutionary Bioinformatics by Nick T. Thomopoulos
Cover of the book Composing Fisher Kernels from Deep Neural Models by Nick T. Thomopoulos
Cover of the book Brand Gender by Nick T. Thomopoulos
Cover of the book Standardized Hierarchical Vegetation Classification by Nick T. Thomopoulos
Cover of the book Music Learning and Teaching in Culturally and Socially Diverse Contexts by Nick T. Thomopoulos
Cover of the book Jerome S. Bruner beyond 100 by Nick T. Thomopoulos
Cover of the book Software Quality. The Future of Systems- and Software Development by Nick T. Thomopoulos
Cover of the book Post-Quantum Cryptography by Nick T. Thomopoulos
Cover of the book Beneficial Plant-Bacterial Interactions by Nick T. Thomopoulos
Cover of the book Protocols and Methodologies in Basic Science and Clinical Cardiac MRI by Nick T. Thomopoulos
Cover of the book Algorithms and Discrete Applied Mathematics by Nick T. Thomopoulos
Cover of the book Practical Guide to Paraphilia and Paraphilic Disorders by Nick T. Thomopoulos
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy