The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo MCMC. Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.

    With a cruel council leading the only safe city of it's kind in this world, she will have to prove her worth to stay as well as help this city as it is the target for two evil wizards who seek to destroy the city and it's ruling council.Will the council's mighty army of guardians be enough to repel the onslaught of the two wizards' wrath?To help the city and also get back home, she will need the help of the greatest mathematician of all time, Archimedes. In a world where math is magic, Alex wishes she paid more attention in math class.

    Therefore, this book provides the fundamental concepts and techniques of real analysis for readers in all of these areas. It helps one develop the ability to think deductively, analyze mathematical situations and extend ideas to a new context. Like the first two editions, this edition maintains the same spirit and user-friendly approach with some streamlined arguments, a few new examples, rearranged topics, and a new chapter on the Generalized Riemann Integral.

    Notes and activities reflect the way that teachers teach now and include shared texts, guided reading notes, reading activities, speaking and listening activities, writing projects and assessment guidance.

    The presentation is never awkward or dry, as it sometimes is in other "modern" textbooks; it is as unconventional as one has come to expect from the author. The book contains about 350 well placed and instructive problems, which cover a considerable part of the subject. All in all, this is an excellent work, of equally high value for both student and teacher." Zentralblatt f�r Mathematik

    It demonstrates how to encourage, develop, and foster the processes which seem to come naturally to mathematicians.

    In Making Numbers Count, Chip Heath argues that it's crucial for us all to be able to interpret and communicate numbers and stats more effectively so that data comes alive. By combining years of research into making ideas stick with a deep understanding of how the brain really works, Heath has discerned six critical principles that will give anyone the tools to communicate numbers with more transparency and meaning. These ideas - including simplicity, concreteness and familiarity - reveal what's compelling about a number and show how to transform it into its most understandable form. And if we can do this when we're using numbers, Heath tells us, then the idea of data won't drive people to panic. We're not hungry for numbers - there's an unfathomable amount of information being generated each year - but we are starved for meaning. The ability to communicate and understand numbers has never mattered more.

    Cases, datasets, and examples allow for a more real-world perspective and explore relevant uses of regression techniques in business today.

    The aim of a course in real analysis should be to challenge and improve mathematical intuition rather than to verify it. The philosophy of this book is to focus attention on questions which give analysis its inherent fascination.

     Building Thinking Classrooms in Mathematics, Grades K-12 helps teachers implement 14 optimal practices for thinking that create an ideal setting for deep mathematics learning to occur. This guideProvides the what, why, and how of each practice Includes firsthand accounts of how these practices foster thinking Offers a plethora of macro moves, micro moves, and rich tasks to get started

    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.

    At the time we were hoping that our approach of writing a book which would be both accessible without mathematical sophistication and portray these exiting new fields in an authentic manner would find an audience. Now we know it did. We know from many reviews and personal letters that the book is used in a wide range of ways: researchers use it to acquaint themselves, teachers use it in college and university courses, students use it for background reading, and there is also a substantial audience of lay people who just want to know what chaos and fractals are about. Every book that is somewhat technical in nature is likely to have a number of misprints and errors in its first edition. Some of these were caught and brought to our attention by our readers. One of them, Hermann Flaschka, deserves to be thanked in particular for his suggestions and improvements. This second edition has several changes. We have taken out the two appendices from the firstedition. At the time of the first edition Yuval Fishers contribution, which we published as an appendix was probably the first complete expository account on fractal image compression. Meanwhile, Yuvals book Fractal Image Compression: Theory and Application appeared and is now the publication to refer to.

    The presentation stresses analytical methods, concrete examples, and geometric intuition. A unique feature of the book is its emphasis on applications. These include mechanical vibrations, lasers, biological rhythms, superconducting circuits, insect outbreaks, chemical oscillators, genetic control systems, chaotic waterwheels, and even a technique for using chaos to send secret messages. In each case, the scientific background is explained at an elementary level and closely integrated with mathematical theory.About the Author:Steven Strogatz is in the Center for Applied Mathematics and the Department of Theoretical and Applied Mathematics at Cornell University. Since receiving his Ph.D. from Harvard university in 1986, Professor Strogatz has been honored with several awards, including the E.M. Baker Award for Excellence, the highest teaching award given by MIT.

    Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

    Includes expert coverage of new topics: Turbocodes, Turboequalization, Antenna Arrays, Digital Cellular Systems, and Iterative Detection. Convenient, sequential organization begins with a look at the historyo and classification of channel models and builds from there.