The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    These sections together make an appropriate one-term advanced/graduate level course (mathematical prerequisites: vector analysis and simple partial-differential equations). The book is printed to make it easy for readers to identify these sections.• The remaining Track 2 material provides a wealth of advanced topics instructors can draw from to flesh out a two-term course, with Track 1 sections serving as prerequisites.

    But all too often, even the most respected publications present numbers that are miscalculated, misinterpreted, hyped, or simply misleading. Following on the heels of his highly acclaimed Damned Lies and Statistics and More Damned Lies and Statistics, Joel Best now offers this practical field guide to help everyone identify questionable statistics. Entertaining, informative, and concise, Stat-Spotting is essential reading for people who want to be more savvy and critical consumers of news and information.Stat-Spotting features:* Pertinent examples from today's news, including the number of deaths reported in Iraq, the threat of secondhand smoke, the increase in the number of overweight Americans, and many more* A commonsense approach that doesn't require advanced math or statistics

    It is also a wakeup call about the dubious origins of food labeled organic. After eating some suspect organic walnuts that supposedly were produced in Kazakhstan, veteran journalist Peter Laufer chooses a few items from his home pantry and traces their origins back to their source. Along the way he learns how easily we are tricked into taking “organic” claims at face value.With organic foods readily available at supermarket chains, confusion and outright deception about labels have become commonplace. Globalization has allowed food from highly corrupt governments and businesses overseas to pollute the organic market with food that is anything but. The organic environment is like the Wild West: oversight is virtually nonexistent, and deception runs amok. Laufer investigates so-called organic farms in Europe and South America as well as in his own backyard in the Pacific Northwest.The book examines what constitutes organic and by whom the definitions are made. The answers will stun readers, who have been sold a questionable, highly suspect, and even false bill of goods for years.

    From cell ultrastructure and carbohydrates to amino acids, proteins, and supramolecular structure, you'll identify biochemical structures and reactions, and send your grades soaring.Newest biology, biochemistry, chemistry, and scientific discoveries;Updated examples and explanations;Incorporates the most current teaching techniques;From water biochemistry to protein synthesis, Biochemistry For Dummies gives you the vital information, clear explanations, and important insights you need to increase your understanding and improve your performance on any biochemistry test.

    There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor M. G. Bulmer's Principles of Statistics, originally published in 1965, was created to fill that need. The new, corrected Dover edition of Principles of Statistics makes this invaluable mid-level text available once again for the classroom or for self-study.Principles of Statistics was created primarily for the student of natural sciences, the social scientist, the undergraduate mathematics student, or anyone familiar with the basics of mathematical language. It assumes no previous knowledge of statistics or probability; nor is extensive mathematical knowledge necessary beyond a familiarity with the fundamentals of differential and integral calculus. (The calculus is used primarily for ease of notation; skill in the techniques of integration is not necessary in order to understand the text.)Professor Bulmer devotes the first chapters to a concise, admirably clear description of basic terminology and fundamental statistical theory: abstract concepts of probability and their applications in dice games, Mendelian heredity, etc.; definitions and examples of discrete and continuous random variables; multivariate distributions and the descriptive tools used to delineate them; expected values; etc. The book then moves quickly to more advanced levels, as Professor Bulmer describes important distributions (binomial, Poisson, exponential, normal, etc.), tests of significance, statistical inference, point estimation, regression, and correlation. Dozens of exercises and problems appear at the end of various chapters, with answers provided at the back of the book. Also included are a number of statistical tables and selected references.

    The book also provides a balanced presentation of time-varying and static fields, preparingstudents for employment in today's industrial and manufacturing sectors. Streamlined to facilitate student understanding, this edition features worked examples in every chapter that explain how to use the theory presented in the text to solve different kinds of problems. Numerical methods, including MATLAB and vector analysis, are also included to help students analyzesituations that they are likely to encounter in industry practice. Elements of Electromagnetics, Fifth Edition, is designed for introductory undergraduate courses in electromagnetics.

    Collected here to keep your wits sharp, The Best Brain Teasers of All Time features the cleverest brain teasers from around the world and throughout history.The Best Brain Teasers of All Time gives you hours of fun-filled entertainment with brain teasers that develop your problem-solving skills in math, logic, and wordplay. Organized as an integrated challenge, these brain teasers build in momentum as they increase in difficulty from classic nursery rhymes to the riddle of the sphinx.The Best Brain Teasers of All Time puts your mind to the test with: 125 Brain Teasers that require no special skills to solve. Plus, each question comes with an optional clue in case you get stumped and a handy answer key in the back to test yourself or play with friends Brain Teasers for Every Level that cater to beginners and advanced masterminds alike, with brain teasers organized by level of difficulty to improve your skills as you move forward Hints of History that provide fun facts and background information for every brain teaser Get ready to sharpen your wit with every “aha” moment. The Best Brain Teasers of All Time is a go-to source for timeless fun and mind-blowing challenges.

    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.

    The authors have eliminated unnecessary mathematical detail and concentrate on the intuition and insights that will be useful to practitioners throughout their careers as new ideas and challenges emerge from the financial marketplace. Essentials maintains the theme of asset allocation (authors discuss asset pricing and trading then apply these theories to portfolio planning in real-world securities markets that are governed by risk/return relationships).

    The 7th edition incorporates the latest advances in molecular diagnostics, the Human Genome Project, and much more. More than 240 dynamic illustrations and high-quality photos help you grasp complex concepts more easily. In addition to the book, you will also receive STUDENT CONSULT, enabling you to access the complete contents of the book online, anywhere you go

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

    This book covers game theory, economics of Information, and behavioral economics, using examples that cover such topics as the analysis of demand, cost, and market efficiency; the design of pricing strategies; and public policy analysis.

    It introduces marketing from the perspective of real people making real marketing decisions at leading companies "every day. "Learners will come to understand that marketing is about "creating value"-for customers, for companies, and for society as a whole-and they will see how that is accomplished in the real world. A five-part organization covers making marketing value decisions, identifying markets and understanding customers' needs for value, creating the value proposition, communicating the value proposition, and delivering the value proposition. For individuals interested in a career in marketing.

    No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and more Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.