The CRC Handbook of Tables for the Use of Order Statistics in Estimation revises and significantly expands upon the well-known Order Statistics and Their Use in Testing and Estimation (Volume 2), published in 1970. It brings together tables relating to order statistics from many important distributions and provides maximum likelihood estimations of their parameters based on complete as well as Type-II censored samples. This practical reference describes in detail the method of computation used to construct the tables and illustrates their usefulness with practical examples. The CRC Handbook of Tables for the Use of Order Statistics in Estimation is easy to use and provides information on order statistics estimation at your fingertips.

First derived within the context of life-testing, inverse Gaussian distribution has become one of the most important and widely employed distributions, and is often used to model the lifetimes of components. It is also used as a model in many varied applications, including fatigue analysis, economic prediction analysis, and the analysis of extreme events such as rainfall and flood levels. The interesting features and properties of this distribution make it an important and realistic model in a variety of problems across numerous disciplines. Because of the broad range of applications, this handbook will be useful not only to members of the statistical community but will also appeal to applied scientists, engineers, econometricians, and anyone who desires a thorough evaluation of this important topic.

Lognormal distributions are one of the most commonly studied models in the sta tistical literature while being most frequently used in the applied literature. The lognormal distributions have been used in problems arising from such diverse fields as hydrology, biology, communication engineering, environmental science, reliability, agriculture, medical science, mechanical engineering, material science, and pharma cology. Though the lognormal distributions have been around from the beginning of this century (see Chapter 1), much of the work concerning inferential methods for the parameters of lognormal distributions has been done in the recent past. Most of these methods of inference, particUlarly those based on censored samples, involve extensive use of numerical methods to solve some nonlinear equations. Order statistics and their moments have been discussed quite extensively in the literature for many distributions. It is very well known that the moments of order statistics can be derived explicitly only in the case of a few distributions such as exponential, uniform, power function, Pareto, and logistic. In most other cases in cluding the lognormal case, they have to be numerically determined. The moments of order statistics from a specific lognormal distribution have been tabulated ear lier. However, the moments of order statistics from general lognormal distributions have not been discussed in the statistical literature until now primarily due to the extreme computational complexity in their numerical determination.

A companion volume to the authors' previous well-received work, the CRC Handbook of Tables for the Use of Order Statistics in Estimation, this handbook discusses testing whether a hypothesis is true or false. Together, these volumes are your complete reference to theory and important tables relating to order statistics and their applications. Once a researcher completes an experiment, the resulting data is assumed to have come from a normal distribution with its mean and variance unknown. The researcher is then presented with a hypothesis testing problem. The use of order statistics and related functions offers a simple, powerful, and interesting approach to solving this problem. This volume presents an introduction to the use of order statistics and explains the various problems and their applications. The role of order statistics in solving these problems is examined, several important statistics are introduced, and their use in addressing testing of hypothesis problems is highlighted. The book also includes numerous tables that facilitate the methods of hypothesis testing using order statistics. Examples are given of the use of these tables in multiple comparison tests, with attention to error rates and sample sizes, and in the analog range of analysis of variance.

Compilation of statistical tables for use in probability and statistical method.

Descriptive Statistics; Probability; Multivariate distributions; Probability distributions; Analysis of variance; General linear model; Normal distribution; Binomial, Poisson, hipergeometric and negative binomial distribution; Student's t-distribution; Chi-Square distribution; f-Distribution; Order statistics; Range and studentized range; Correlation coefficient; Non-parametric statistics; Quality control; Miscellaneous statistical tables; Miscellaneous mathematical tables.