Handbook of Statistical Distributions with Applications (2^nd Ed.)
Statistics: A Series of Textbooks and Monographs Series

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.

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.