Politicians and marketers present shoddy evidence for dubious claims all the time. But smart people make mistakes too, and when it comes to statistics, plenty of otherwise great scientists--yes, even those published in peer-reviewed journals--are doing statistics wrong."Statistics Done Wrong" comes to the rescue with cautionary tales of all-too-common statistical fallacies. It'll help you see where and why researchers often go wrong and teach you the best practices for avoiding their mistakes.In this book, you'll learn: - Why "statistically significant" doesn't necessarily imply practical significance- Ideas behind hypothesis testing and regression analysis, and common misinterpretations of those ideas- How and how not to ask questions, design experiments, and work with data- Why many studies have too little data to detect what they're looking for-and, surprisingly, why this means published results are often overestimates- Why false positives are much more common than "significant at the 5% level" would suggestBy walking through colorful examples of statistics gone awry, the book offers approachable lessons on proper methodology, and each chapter ends with pro tips for practicing scientists and statisticians. No matter what your level of experience, "Statistics Done Wrong" will teach you how to be a better analyst, data scientist, or researcher.

    These 30 short chapters each deal with a particular programming problem drawn from sources as diverse as games and puzzles, intriguing combinatorial tasks, and more familiar areas such as data compression and string matching. Each pearl starts with the statement of the problem expressed using the functional programming language Haskell, a powerful yet succinct language for capturing algorithmic ideas clearly and simply. The novel aspect of the book is that each solution is calculated from an initial formulation of the problem in Haskell by appealing to the laws of functional programming. Pearls of Functional Algorithm Design will appeal to the aspiring functional programmer, students and teachers interested in the principles of algorithm design, and anyone seeking to master the techniques of reasoning about programs in an equational style.

    The text converts all programming code into the C++ language.

    It is the only book that gives a full introduction to programming in MATLAB combined with an explanation of MATLAB's powerful functions. The book differs from other texts in that it teaches programming concepts and the use of the built-in functions in MATLAB simultaneously. It presents programming concepts and MATLAB built-in functions side-by-side, giving students the ability to program efficiently and exploit the power of MATLAB to solve problems. The systematic, step-by-step approach, building on concepts throughout the book, facilitates easier learning.Starting with basic programming concepts, such as variables, assignments, input/output, selection, and loop statements, problems are introduced and solved throughout the book. The book is organized into two parts. Part I covers the programming constructs and demonstrates programming versus efficient use of built-in functions to solve problems. Part II describes the applications, including plotting, image processing, and mathematics, needed in basic problem solving. The chapters feature sections called Quick Question! as well as practice problems designed to test knowledge about the material covered. Problems are solved using both The Programming Concept and The Efficient Method, which facilitates understanding the efficient ways of using MATLAB, and also the programming concepts used in these efficient functions and operators. There are also sections on 'common pitfalls' and 'programming guidelines' that direct students towards best practice.This book is ideal for engineers learning to program and model in MATLAB, as well as undergraduates in engineering and science taking a course on MATLAB.

    Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer winning in games like Jeopardy and go does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules. These approaches are too narrow to achieve genuine intelligence. The world we live in is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Marcus and Davis show us what we need to first accomplish before we get there and argue that if we are wise along the way, we won't need to worry about a future of machine overlords. If we heed their advice, humanity can create an AI that we can trust in our homes, our cars, and our doctor's offices. Reboot provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of what we can achieve and how AI can make our lives better.

    Widely recognized as the most comprehensive, accessible and practical basis for scientific computing, this new edition incorporates more than 400 Numerical Recipes routines, many of them new or upgraded. The executable C++ code, now printed in color for easy reading, adopts an object-oriented style particularly suited to scientific applications. The whole book is presented in the informal, easy-to-read style that made earlier editions so popular. Please visit www.nr.com or www.cambridge.org/us/numericalrecipes for more details. More information concerning licenses is available at: www.nr.com/licenses New key features: 2 new chapters, 25 new sections, 25% longer than Second Edition Thorough upgrades throughout the text Over 100 completely new routines and upgrades of many more. New Classification and Inference chapter, including Gaussian mixture models, HMMs, hierarchical clustering, Support Vector MachinesNew Computational Geometry chapter covers KD trees, quad- and octrees, Delaunay triangulation, and algorithms for lines, polygons, triangles, and spheres New sections include interior point methods for linear programming, Monte Carlo Markov Chains, spectral and pseudospectral methods for PDEs, and many new statistical distributions An expanded treatment of ODEs with completely new routines Plus comprehensive coverage of linear algebra, interpolation, special functions, random numbers, nonlinear sets of equations, optimization, eigensystems, Fourier methods and wavelets, statistical tests, ODEs and PDEs, integral equations, and inverse theory

    Widely accepted as the authoritative text and reference on electronic circuit design, both analog and digital, this book revolutionized the teaching of electronics by emphasizing the methods actually used by circuit designers -- a combination of some basic laws, rules of thumb, and a large bag of tricks. The result is a largely nonmathematical treatment that encourages circuit intuition, brainstorming, and simplified calculations of circuit values and performance. The new Art of Electronics retains the feeling of informality and easy access that helped make the first edition so successful and popular. It is an ideal first textbook on electronics for scientists and engineers and an indispensable reference for anyone, professional or amateur, who works with electronic circuits.

    Albert-László Barabási, the nation’s foremost expert in the new science of networks and author of Bursts, takes us on an intellectual adventure to prove that social networks, corporations, and living organisms are more similar than previously thought. Grasping a full understanding of network science will someday allow us to design blue-chip businesses, stop the outbreak of deadly diseases, and influence the exchange of ideas and information. Just as James Gleick and the Erdos–Rényi model brought the discovery of chaos theory to the general public, Linked tells the story of the true science of the future and of experiments in statistical mechanics on the internet, all vital parts of what would eventually be called the Barabási–Albert model.

    If you're a business or IT professional, this short hands-on guide teaches you how to pull and transform data with SQL in significant ways. You will quickly master the fundamentals of SQL and learn how to create your own databases.Author Thomas Nield provides exercises throughout the book to help you practice your newfound SQL skills at home, without having to use a database server environment. Not only will you learn how to use key SQL statements to find and manipulate your data, but you'll also discover how to efficiently design and manage databases to meet your needs.You'll also learn how to:Explore relational databases, including lightweight and centralized modelsUse SQLite and SQLiteStudio to create lightweight databases in minutesQuery and transform data in meaningful ways by using SELECT, WHERE, GROUP BY, and ORDER BYJoin tables to get a more complete view of your business dataBuild your own tables and centralized databases by using normalized design principlesManage data by learning how to INSERT, DELETE, and UPDATE records

    

    It provides many detailed, practical design and analysis examples intended to relate theory to the workplace. Chapter topics include first experiences with an op amp; inverting and noninverting amplifiers; comparators and controls; selected applications of op amps; signal generators; op amps with diodes; differential, instrumentation, and bridge amplifiers; DC performance: bias, offsets, and drift; AC performance: bandwidth, slew rate, noise; active filters; modulating, demodulating, and frequency changing with the multiplier; integrated-circuit timers; digital-to-analog converters; analog-to-digital converters; and power supplies. For design engineers rs

    It combines the nice features of a scripting language with the powerful features of a production environment—features like persistent data structures and clean multithreading that you'll need for industrial-strength application development.The Joy of Clojure goes beyond just syntax to show you how to write fluent and idiomatic Clojure code. You'll learn a functional approach to programming and will master Lisp techniques that make Clojure so elegant and efficient. The book gives you easy access to hard soft ware areas like concurrency, interoperability, and performance. And it shows you how great it can be to think about problems the Clojure way. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's InsideThe what and why of ClojureHow to work with macrosHow to do elegant application designFunctional programming idiomsWritten for programmers coming to Clojure from another programming background—no prior experience with Clojure or Lisp is required.

    “Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior.In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing.www.big-data-book.com

    Its humorous title begins with the punch line of a classic joke about someone who is baffled by technology. It was written by a 40-year computer veteran who wants to take the mystery out of computers and allow everyone to gain a true understanding of exactly what computers are, and also what they are not. Years of writing, diagramming, piloting and editing have culminated in one easy to read volume that contains all of the basic principles of computers written so that everyone can understand them. There used to be only two types of book that delved into the insides of computers. The simple ones point out the major parts and describe their functions in broad general terms. Computer Science textbooks eventually tell the whole story, but along the way, they include every detail that an engineer could conceivably ever need to know. Like Momma Bear's porridge, But How Do It Know? is just right, but it is much more than just a happy medium. For the first time, this book thoroughly demonstrates each of the basic principles that have been used in every computer ever built, while at the same time showing the integral role that codes play in everything that computers are able to do. It cuts through all of the electronics and mathematics, and gets right to practical matters. Here is a simple part, see what it does. Connect a few of these together and you get a new part that does another simple thing. After just a few iterations of connecting up simple parts - voilà! - it's a computer. And it is much simpler than anyone ever imagined. But How Do It Know? really explains how computers work. They are far simpler than anyone has ever permitted you to believe. It contains everything you need to know, and nothing you don't need to know. No technical background of any kind is required. The basic principles of computers have not changed one iota since they were invented in the mid 20th century. "Since the day I learned how computers work, it always felt like I knew a giant secret, but couldn't tell anyone," says the author. Now he's taken the time to explain it in such a manner that anyone can have that same moment of enlightenment and thereafter see computers in an entirely new light.

    Beginning with an introduction to array formulas, this manual examines topics such as how they differ from ordinary formulas, the benefits and drawbacks of their use, functions that can and cannot handle array calculations, and array constants and functions. Among the practical applications surveyed include how to extract data from tables and unique lists, how to get results that match any criteria, and how to utilize various methods for unique counts. This book contains 529 screen shots.