Easy-to-Use Reference and Software for Statistical Modeling and Testing
Handbook of Statistical Distributions with Applications, Second Edition provides quick access to common and specialized probability distributions for modeling practical problems and performing statistical calculations. Along with many new examples and results, this edition includes both the author’s StatCalc software and R codes to accurately and easily carry out computations.
New to the Second Edition
- Major changes in binomial, Poisson, normal, gamma, Weibull, exponential, logistic, Laplace, and Pareto distributions
- Updated statistical tests and intervals based on recent publications in statistical journals
- Enhanced PC calculator StatCalc with electronic help manuals
- R functions for cases where StatCalc is not applicable, with the codes available online
This highly praised handbook integrates popular probability distribution models, formulas, applications, and software to help you compute a variety of statistical intervals. It covers probability and percentiles, algorithms for random number generation, hypothesis tests, confidence intervals, tolerance intervals, prediction intervals, sample size determination, and much more.
Table of Contents
StatCalc. Preliminaries. Discrete uniform distribution. Binomial distribution. Hypergeometric distribution. Poisson distribution. Geometric distribution. Negative binomial distribution. Logarithmic series distribution. Continuous uniform distribution. Normal distribution. Chi-square distribution. F Distribution. Student’s t distribution. Exponential distribution. Gamma distribution. Beta distribution. Noncentral chi-square distribution. Noncentral F distribution. Noncentral t distribution. Laplace distribution. Logistic distribution. Lognormal distribution. Pareto distribution. Weibull distribution. Extreme value distribution. Cauchy distribution. Inverse Gaussian distribution. Rayleigh distribution. Bivariate normal distribution. Some nonparametric methods.
Kalimuthu Krishnamoorthy, Ph.D., is a professor of statistics and SLEMCO Professor of Science at the University of Louisiana at Lafayette. He is an elected fellow of the American Statistical Association and an associate editor of Communications in Statistics. He has published more than 100 articles relating to small sample inference, multivariate analysis, fiducial inference, and statistical methods for exposure data analysis.
Praise for the First Edition:
"… the book has a chance of becoming a highly valued practitioner’s reference …"
"The book is sequentially organized and well structured and many chapters are self-contained. It includes many useful results that are handy for students and practitioners alike....I must say, it is a very useful and handy book for commonly used probability distributions, a one-stop shop! ...this is a valuable contribution to [the] scientific community, providing up-to-date coverage on probability distributions and their applications in a systematic fashion. I would like to see this book on my desk! -S.E. Ahmed, Technometrics, July 2016
Journal of the Royal Statistical Society
"I recommend the StatCalc software as a useful quick way to obtain and/or check (relative) simple statistical calculations, and the book as its accompanying manual … many statisticians might find StatCalc a handy addition to their computer desktops, particularly (in my case) with teaching in mind!"
—M.C. Jones, Journal of Applied Statistics, January 2008
"… recommended to statistical practitioners who need a comprehensive yet brief reference on statistical distributions with applications."
—Brian Wiens, The American Statistician, November 2007
"Quite simply, this book is a masterwork. … an essential resource for anyone who models data, or creates applications that require reference to or make use of statistical distribution functions or random variable sampling/generation. The accompanying PC program is a true application in its own right: neat, tidy, and very, very useful. To have this and the book represents a unique reference work. … easily understandable by undergraduate as well as graduate scientists and statisticians … an essential part of the toolkit for professionals working in the quantitative sciences … a remarkable achieveme