Rigorous yet accessible, Logical Methods introduces logical tools used in philosophy—including proofs, models, modal logics, meta-theory, two-dimensional logics, and quantification—for philosophy students at the undergraduate level and above. The approach developed by Greg Restall and Shawn Standefer is distinct from other texts because it presents proof construction on equal footing with model building and emphasizes connections to other areas of philosophy as the tools are developed.Throughout, the material draws on a broad range of examples to show readers how to develop and master tools of proofs and models for propositional, modal, and predicate logic; to construct and analyze arguments and to find their structure; to build counterexamples; to understand the broad sweep of formal logic’s development in the twentieth and twenty-first centuries; and to grasp key concepts used again and again in philosophy.This text is essential to philosophy curricula, regardless of specialization, and will also find wide use in mathematics and computer science programs.

The eighth edition of Chapra and Canale's Numerical Methods for Engineers retains the instructional techniques that have made the text so successful. The book covers the standard numerical methods employed by both students and practicing engineers. Although relevant theory is covered, the primary emphasis is on how the methods are applied for engineering problem solving. Each part of the book includes a chapter devoted to case studies from the major engineering disciplines. Numerous new or revised end-of chapter problems and case studies are drawn from actual engineering practice. This edition also includes several new topics including a new formulation for cubic splines, Monte Carlo integration, and supplementary material on hyperbolic partial differential equations.

A Practical Approach to using Multivariate Analyses Using Multivariate Statistics, 6th edition provides advanced undergraduate as well as graduate students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics. This text’s practical approach focuses on the benefits and limitations of applications of a technique to a data set – when, why, and how to do it. Learning GoalsUpon completing this book, readers should be able to: Learn to conduct numerous types of multivariate statistical analyses Find the best technique to use Understand Limitations to applications Learn how to use SPSS and SAS syntax and output