But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

    It strikes a balance between theory and application by incorporating real-world examples; helping students visualize the three-dimensional atomic and molecular structures that are the basis of chemical activity; and developing problem-solving and critical thinking skills. Although the fifth edition incorporates many new features, such as macro to micro artwork, six new animations correlated to the text, and the addition of new hand-sketched worked examples, General Chemistry is still 200 to 300 pages shorter and much less expensive than other two-semester textbooks. Dr. Chang's concise-but-thorough approach will appeal to efficiency-minded instructors and value-conscious students.

    The unique on-line grading services instantly grades solutions to hundred of computer exercises. It is specially devised to be used by philosophy instructors in a way that is useful to undergraduates of philosophy, computer science, mathematics, and linguistics.The book is a completely rewritten and much improved version of The Language of First-order Logic. Introductory material is presented in a more systematic and accessible fashion. Advanced chapters include proofs of soundness and completeness for propositional and predicate logic, as well as an accessible sketch of Godel's first incompleteness theorem. The book is appropriate for a wide range of courses, from first logic courses for undergraduates (philosophy, mathematics, and computer science) to a first graduate logic course.The package includes four pieces of software:Tarski's World 5.0, a new version of the popular program that teaches the basic first-order language and its semantics; Fitch, a natural deduction proof environment for giving and checking first-order proofs;Boole, a program that facilitates the construction and checking of truth tables and related notions (tautology, tautological consequence, etc.);Submit, a program that allows students to submit exercises done with the above programs to the Grade Grinder, the automatic grading service.Grade reports are returned to the student and, if requested, to the student's instructor, eliminating the need for tedious checking of homework. All programs are available for Windows, Macintosh and Linux systems.Instructors do not need to use the programs themselves in order to be able to take advantage of their pedagogical value. More about the software can be found at lpl.stanford.edu.The price of a new text/software package includes one Registration ID, which must be used each time work is submitted to the grading service. Once activated, the Registration ID is not transferable.

    It was a popular winter destination for North American tourists in the 1950s, and this cookbook recaptures the spirit of Old Havana-- Habana la vieja-- and its celebrated culinary traditions. Cuban cuisine, though derived from its mother country, Spain, has been modified and refined by locally available foods like pork, rice, corn, beans and sugar, and the requirements of a tropical climate. Fine Gulf Stream fish, crabs and lobsters, and an almost infinite variety of vegetables and luscious tropical fruits also have their places on the traditional Cuban table. This cookbook includes over 50 recipes, each in Spanish with side-by-side English translation-- all of them classic Cuban fare and old Havana specialties adapted for the North American kitchen. Among the recipes included are: Ajiaco (famous Cuban Stew), Boiled Pargo with Avocado Sauce, Lobster Havanaise, Tamal en Cazuela (Soft Tamal), Quimbombo (okra), Picadillo, Roast Suckling Pig, and Boniatillo (Sweet Potato Dulce), along with a whole chapter on famous Cuban cocktails and beverages.

    Updated and revised for iPhone SDK 3, many of the discussions in the original book have been clarified to make some of the more complex topics easier to understand. In addition, all of the projects have been rebuilt from scratch using the SDK 3 templates.Assuming only a minimal working knowledge of Objective-C, and written in a friendly, easy-to-follow style, this book offers a complete soup-to-nuts course in iPhone and iPod touch programming. The book starts with the basics, walking you through the process of downloading and installing Apple's free iPhone SDK, and then stepping you though the creation of your first simple iPhone application. From there, you'll learn to integrate all the interface elements iPhone users have come to know and love, such as buttons, switches, pickers, toolbars, and sliders. You'll master a variety of design patterns, from the simplest single view to complex hierarchical drill-downs. The confusing art of table building will be demystified, and you'll see how to save your data using the iPhone file system. You'll also learn how to save and retrieve your data using SQLite, iPhone's built-in database management system. In addition, you'll also learn about Core Data, an important persistence mechanism that has just been added with SDK 3.And there's much more! You'll learn to draw using Quartz 2D and OpenGL ES, add multitouch gestural support (pinches and swipes) to your applications, and work with the camera, photo library, accelerometer, and built-in GPS. You'll discover the fine points of application preferences and learn how to localize your apps for multiple languages. You can discover more about this book, download source code, and find support forums at the book's companion site, at www.iphonedevbook.com.The iPhone 3 update to the best-selling and most recommended book for iPhone developers Packed full of tricks, techniques, and enthusiasm for the new SDK from a developer perspective The most complete, useful, and up-to-date guide to all things having to do with Apple's iPhone SDK

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    This respected title is also one of the National League for Nursing's recommended resources for nurses preparing to take the Certified Nurse Educator examination.Nationally recognized contributing authors share their expertise to bring you the best and most comprehensive information available.Presents innovative models of clinical teaching that show you how to effectively teach in an interdisciplinary setting, how to evaluate students in the clinical setting, and how to adapt your teaching for community-based practice.li>Strategies to promote critical thinking and active learning, including evaluation techniques, lesson planning, and constructing examinations, help you ensure students can apply and synthesize nursing content to make clinical decisions.li>Web links with numerous resources related to each chapter topic, available through the Evolve website, provide even more learning opportunities.Managing the Learning Environment chapter addresses classroom management and control, motivating and engaging students, and handling disruptive or problem students.Multicultural Education chapter provides strategies for effectively teaching and communicating with a culturally diverse student population.An entire chapter on simulations presents the development, implementation, and evaluation of simulations so you can successfully integrate this teaching method into your course.Reflecting on the Evidence feature at the end of each chapter provides questions that are perfect for classroom and online discussion.

    It uses examples and exercise sets, with clear explanations of problem-solving techniqes and material on the further theory of functions.

    The book s two-part coverage organizes topics under basic theory, and assembles an arsenal of approximation schemes with illustrative applications. For physicists and engineers. "

    Aimed at undergraduate students in mathematics, physics, and engineering, the book's intuitive explanations, lack ofadvanced prerequisites, and consciously user-friendly prose style will help students to master the subject more readily than was previously possible. The key to this is the book's use of new geometric arguments in place of the standard calculational ones. These geometric arguments are communicatedwith the aid of hundreds of diagrams of a standard seldom encountered in mathematical works. A new approach to a classical topic, this work will be of interest to students in mathematics, physics, and engineering, as well as to professionals in these fields.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    Renowned for her lucid, accessible prose, Epp explains complex, abstract concepts with clarity and precision. This book presents not only the major themes of discrete mathematics, but also the reasoning that underlies mathematical thought. Students develop the ability to think abstractly as they study the ideas of logic and proof. While learning about such concepts as logic circuits and computer addition, algorithm analysis, recursive thinking, computability, automata, cryptography, and combinatorics, students discover that the ideas of discrete mathematics underlie and are essential to the science and technology of the computer age. Overall, Epp's emphasis on reasoning provides students with a strong foundation for computer science and upper-level mathematics courses.

    In the modern experimentalist paradigm, these techniques address clear causal questions such as: Do smaller classes increase learning? Should wife batterers be arrested? How much does education raise wages? Mostly Harmless Econometrics shows how the basic tools of applied econometrics allow the data to speak.In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jorn-Steffen Pischke explain why fancier econometric techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science.An irreverent review of econometric essentials A focus on tools that applied researchers use most Chapters on regression-discontinuity designs, quantile regression, and standard errors Many empirical examples A clear and concise resource with wide applications

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    The focus is on algorithms and hence the book is well suited for students in computer science and engineering. Motivation is provided from the application areas: all solutions and techniques from computational geometry are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. For students this motivation will be especially welcome. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement. All the basic techniques and topics from computational geometry, as well as several more advanced topics, are covered. The book is largely self-contained and can be used for self-study by anyone with a basic background in algorithms. In the second edition, besides revisions to the first edition, a number of new exercises have been added.