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"From adjusted gross income to zoning and property taxes, the second edition of The Encyclopedia of Taxation and Tax Policy offers the best and most complete guide to taxes and tax-related issues. More than 150 tax practitioners and administrators, policymakers, and academics have contributed. The result is a unique and authoritative reference that examines virtually all tax instruments used by governments (individual income, corporate income, sales and value-added, property, estate and gift, franchise, poll, and many variants of these taxes), as well as characteristics of a good tax system, budgetary issues, and many current federal, state, local, and international tax policy issues. The new edition has been completely revised, with 40 new topics and 200 articles reflecting six years of legislative changes. Each essay provides the generalist with a quick and reliable introduction to many topics but also gives tax specialists the benefit of other experts' best thinking, in a manner that makes the complex understandable. Reference lists point the reader to additional sources of information for each topic. The first edition of The Encyclopedia of Taxation and Tax Policy was selected as an Outstanding Academic Book of the Year (1999) by Choice magazine."--Publisher's website.
Foundations and Applications of Statistics simultaneously emphasizes both the foundational and the computational aspects of modern statistics. Engaging and accessible, this book is useful to undergraduate students with a wide range of backgrounds and career goals. The exposition immediately begins with statistics, presenting concepts and results from probability along the way. Hypothesis testing is introduced very early, and the motivation for several probability distributions comes from p-value computations. Pruim develops the students' practical statistical reasoning through explicit examples and through numerical and graphical summaries of data that allow intuitive inferences before introducing the formal machinery. The topics have been selected to reflect the current practice in statistics, where computation is an indispensible tool. In this vein, the statistical computing environment R is used throughout the text and is integral to the exposition. Attention is paid to developing students' mathematical and computational skills as well as their statistical reasoning. Linear models, such as regression and ANOVA, are treated with explicit reference to the underlying linear algebra, which is motivated geometrically. Foundations and Applications of Statistics discusses both the mathematical theory underlying statistics and practical applications that make it a powerful tool across disciplines. The book contains ample material for a two-semester course in undergraduate probability and statistics. A one-semester course based on the book will cover hypothesis testing and confidence intervals for the most common situations. In the second edition, the R code has been updated throughout to take advantage of new R packages and to illustrate better coding style. New sections have been added covering bootstrap methods, multinomial and multivariate normal distributions, the delta method, numerical methods for Bayesian inference, and nonlinear least squares. Also, the use of matrix algebra has been expanded, but remains optional, providing instructors with more options regarding the amount of linear algebra required.