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Overview
This book contains several new or unpublished tables, such as one on the significance of the correlation coefficient r, one giving the percentiles of the (2 statistic for monotonic variation (with two structural models of variation), an extensive table for the number-of-runs test, three tables for the binomial sum of probabilities, and a table of coefficients for the re-conversion of orthogonal polynomials.In the case of the more familiar tables, such as those of the normal integral, or Student's t, Chi-square and F percentiles, all values have been re-computed, occasionally with the authors' own algorithms, using the most accurate methods available today.
For each of the fifteen distributions in the book, the authors have gathered the essential information so that interested readers can handle by themselves all phases of the computations.
An appendix, containing supplementary examples that pertain to the various tables, helps to complete the authors' review of current hypothesis-testing procedures. A mini-dictionary of often-used concepts and methods, statistical as well as mathematical, completes the book.
Besides meeting the needs of practitioners of inferential statistics, this book should be helpful to statistics teachers as well as graduate students, researchers and professionals in scientific computing, who will all find it a rich source of essential data and references on the more important statistical distributions.
Synopsis
This book contains several new or unpublished tables, such as one on the significance of the correlation coefficient r, one giving the percentiles of the (2 statistic for monotonic variation (with two structural models of variation), an extensive table for the number-of-runs test, three tables for the binomial sum of probabilities, and a table of coefficients for the re-conversion of orthogonal polynomials.
In the case of the more familiar tables, such as those of the normal integral, or Student's t, Chi-square and F percentiles, all values have been re-computed, occasionally with the authors' own algorithms, using the most accurate methods available today.
For each of the fifteen distributions in the book, the authors have gathered the essential information so that interested readers can handle by themselves all phases of the computations.
An appendix, containing supplementary examples that pertain to the various tables, helps to complete the authors' review of current hypothesis-testing procedures. A mini-dictionary of often-used concepts and methods, statistical as well as mathematical, completes the book.
Besides meeting the needs of practitioners of inferential statistics, this book should be helpful to statistics teachers as well as graduate students, researchers and professionals in scientific computing, who will all find it a rich source of essential data and references on the more important statistical distributions.