This second edition has all the tables required for elementary statistical methods in the social, business and natural sciences.

The latest edition of this very successful and authoritative set of tables, first published in 1984, still benefits from clear typesetting, which makes the figures easy to read and use, but has been improved by the addition of new tables. These give Bayesian confidence limits for the binomial and Poisson distributions, and for the square of the multiple correlation coefficient, which have not been previously available. The intervals are the shortest possible, consistent with the requirement on probability. The authors have taken great care to ensure the clarity of the tables and how their values may be used; the tables are easily interpolated. The book contains all the tables likely to be required for elementary statistical methods in the social, business and natural sciences, and will be an essential aid for teachers, users and students in these areas.

Users of statistics in their professional lives and statistics students will welcome this concise, easy-to-use reference for basic statistics and probability. It contains all of the standardized statistical tables and formulas typically needed plus material on basic statistics topics, such as probability theory and distributions, regression, analysis of variance, nonparametric statistics, and statistical quality control. For each type of distribution the authors supply: ? definitions ? tables ? relationships with other distributions, including limiting forms ? statistical parameters, such as variance and generating functions ? a list of common problems involving the distribution Standard Probability and Statistics: Tables and Formulae also includes discussion of common statistical problems and supplies examples that show readers how to use the tables and formulae to get the solutions they need. With this handy reference, the focus can shift from rote learning and memorization to the concepts needed to use statistics efficiently and effectively.

Now available in a fully revised and updated second edition, this well established textbook provides a straightforward introduction to the theory of probability. The presentation is entertaining without any sacrifice of rigour; important notions are covered with the clarity that the subject demands. Topics covered include conditional probability, independence, discrete and continuous random variables, basic combinatorics, generating functions and limit theorems, and an introduction to Markov chains. The text is accessible to undergraduate students and provides numerous worked examples and exercises to help build the important skills necessary for problem solving.

This book provides a mathematically rigorous introduction to the fundamental ideas of modern statistics for readers without a calculus background.

This Handbook describes the extent and shape of computing education research today. Over fifty leading researchers from academia and industry (including Google and Microsoft) have contributed chapters that together define and expand the evidence base. The foundational chapters set the field in context, articulate expertise from key disciplines, and form a practical guide for new researchers. They address what can be learned empirically, methodologically and theoretically from each area. The topic chapters explore issues that are of current interest, why they matter, and what is already known. They include discussion of motivational context, implications for practice, and open questions which might suggest future research. The authors provide an authoritative introduction to the field which is essential reading for policy makers, as well as both new and established researchers.