Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. This book can be used for readers who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.

    In Intentional Talk: How to Structure and Lead Productive Mathematical Discussions , authors Elham Kazemi and Allison Hintz provide teachers with a framework for planning and facilitating purposeful math talks that move group discussions to the next level while achieving a mathematical goal.Through detailed vignettes from both primary and upper elementary classrooms, the authors provide a window into how teachers lead discussions and make important pedagogical decisions along the way. By creating equitable opportunities to share ideas, teachers can orient students to one another while enforcing that all students are sense makers and their ideas are valued. They examine students’ roles as both listeners and talkers, offering numerous strategies for improving student participation. Intentional Talk includes a collection of lesson planning templates in the appendix to help teachers apply the right structure to discussions in their own classrooms.

    An abundance of applications to current economic analysis, illustrative diagrams, thought-provoking exercises, careful proofs, and a flexible organization-these are the advantages that Mathematics for Economists brings to today’s classroom.

    Including a selection of exercises, adjusted for this edition, at the end of each chapter, it offers a new and simpler treatment of the representability of recursive functions, a traditional stumbling block for students on the way to the Godel incompleteness theorems.

    It is intended to provide the essential primary texts for students of logic, metaphysics and philosophy of language.It contains, in particular, Frege's four essays 'Function and Concept', 'On Sinn and Bedeutung', 'On Concept and Object' and 'Thought', and new translations of key parts of the Begriffschrift, Grundlagen and Grundgesetze. Additional selections have also been made from his Collected Papers, Posthumous Writings and Correspondence. The editor's introduction provides an overview of the development and significance of Frege's philosophy, highlighting some of the main issues of interpretation. Footnotes, appendices and other editorial material have been supplied to facilitate understanding of the works of one of the central figures in modern philosophy.

    John Taylor has brought to his new book, Classical Mechanics, all of the clarity and insight that made his introduction to Error Analysis a best-selling text.

     Offers extensively updated coverage, new problem sets, and chapter-ending material to enhance the book’s relevance to today’s engineers and scientists. Includes new problem sets demonstrating updated applications to engineering as well as biological, physical, and computer science. Emphasizes key ideas as well as the risks and hazards associated with practical application of the material. Includes new material on topics including: difference between discrete and continuous measurements; binary data; quartiles; importance of experimental design; “dummy” variables; rules for expectations and variances of linear functions; Poisson distribution; Weibull and lognormal distributions; central limit theorem, and data plotting. Introduces Bayesian statistics, including its applications to many fields. For those interested in learning more about probability and statistics.

    Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory.All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points.The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated referencesNow current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.

    This work represents the views of a mathematician on the analogies between computing machines and the living human brain.

    Subsequent sections deal with integrating factors; dilution and accretion problems; linearization of first order systems; Laplace Transforms; Newton's Interpolation Formulas, more.

    Included are step-by-step instructions on how to carry out Bayesian data analyses.Download Link : readbux.com/download?i=0124058884            0124058884 Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan PDF by John Kruschke

    With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora

    It includes rewritten and clarified proofs and derivations, as well as new topics such as Arnoldi iteration, and domain decomposition methods.

    It provides comprehensive coverage of the subject from basic principles to state-of-art concepts and applications. The objective is to give the reader a sound understanding of the principles and the basis for applying them in a variety of both product and nonproduct situations. While statistical techniques are emphasized throughout, the book has a strong engineering and management orientation. Guidelines are given throughout the book for selecting the proper type of statistical technique to use in a wide variety of product and nonproduct situations. By presenting theory, and supporting the theory with clear and relevant examples, Montgomery helps the reader to understand the big picture of important concepts. Updated to reflect contemporary practice and provide more information on management aspects of quality improvement.

    What will it take to turn this opportunity into reality in every classroom, school, and district? Continuing its tradition of mathematics education leadership, NCTM has defined and described the principles and actions, including specific teaching practices, that are essential for a high-quality mathematics education for all students. Principles to Actions: Ensuring Mathematical Success for All offers guidance to teachers, specialists, coaches, administrators, policymakers, and parents: Builds on the Principles articulated in Principles and Standards for School Mathematics to present six updated Guiding Principles for School MathematicsSupports the first Guiding Principle, Teaching and Learning, with eight essential, research-based Mathematics Teaching PracticesDetails the five remaining Principles--the Essential Elements that support Teaching and Learning as embodied in the Mathematics Teaching PracticesIdentifies obstacles and unproductive and productive beliefs that all stakeholders must recognize, as well as the teacher and student actions that characterize effective teaching and learning aligned with the Mathematics Teaching PracticesWith Principles to Actions, NCTM takes the next step in shaping the development of high-quality standards throughout the United States, Canada, and worldwide.