What if everything in life could be reduced to a simple formula? What if numbers were able to tell us which partners we were best matched with – not just in terms of attractiveness, but for a long-term committed marriage? Or if they could say which films would be the biggest hits at the box office, and what changes could be made to those films to make them even more successful? Or even who out of us is likely to commit certain crimes, and when? This may sound like the world of science-fiction, but in fact it is just the tip of the iceberg in a world that is increasingly ruled by complex algorithms and neural networks.In The Formula, Luke Dormehl takes you inside the world of numbers, asking how we came to believe in the all-conquering power of algorithms; introducing the mathematicians, artificial intelligence experts and Silicon Valley entrepreneurs who are shaping this brave new world, and ultimately asking how we survive in an era where numbers can sometimes seem to create as many problems as they solve.

    "Using Econometrics: A Practical Guide "provides readers with a practical introduction that combines single-equation linear regression analysis with real-world examples and exercises. This text also avoids complex matrix algebra and calculus, making it an ideal text for beginners. New problem sets and added support make "Using Econometrics" modern and easier to use.

     This area was dangerous and many who had ventured there alone had never returned. But slowly over the course of this century settlers continued to push further west until regions such as West Virginia were populated with more and more adventurous young men and women. The settlement of these lands did not occur without difficulties and colonizers frequently came into conflict with the local Native American populations. Wills De Hass’s remarkable book History of the Early Settlement and Indian Wars of West Virginia is a fascinating history of how the lands of the west were first settled by white emigrants in the eighteenth century and how these settlers came into frequent strife with the Native American tribes who had previously lived there. Beginning with Columbus’ discovery of this great continent Wills De Hass charts the colonization of this expansive land. He records with brilliant detail the early encounters that Europeans had with the men and women that they found already living across the region and explains how various nations from across the Atlantic made their first tentative footholds on this newly discovered land. De Hass records how settlers were not only conflict with Native Americans but also with each other as this region descended into war, firstly during the French and Indian War and shortly afterwards during the American War of Independence. Particularly fascinating throughout the book are the biographical sketches of various well-known frontiersmen who were particularly influential in the Ohio Valley and northwestern Virginia. This book is perfect for anyone interested in the early settlement of western regions prior to 1795 and how this area was frequently in conflict as settlers attempted to assert their rights against the wishes of the Native American populations. Wills de Hass was a lecturer and writer on archaeological and historical subjects. His book History of the Early Settlement and Indian Wars of Western Virginia was first published in 1851 and De Hass passed away 1910.

    It was reduced to dust. Soon I had to admit that there were things far beyond the scope of my rational mind.' What is it that draws one to a mystic? What is it like to know at close quarters a man whose powers are beyond the conscious mind? What does it feel like to be fulfilled spiritually, to feel understood, to stand revealed? As Ismita Tandon and Swami Vidyananda Om explore their feelings for Om Swami, their baffling experiences with him, a secret world of mystical phenomena lights up. They talk about the intimacy of their daily lives with Swami, observing his sheer power, his simplicity, his empathy for every living creature he encounters and the care with which he chooses every word he speaks, no matter how big or small the matter. They speak of his beauty, his divinity. What emerges is a moving portrait of devotion and trust, and the startling image of a saint who was able to inspire such depth of feeling.

    Both are pretty easy to put off as they're very expensive and tend to wreck your house.' Stand-up comedian Sam Avery (aka the Learner Parent) started his award-winning blog when his twin boys were born. A million nappies, Peppa Pig episodes and a lot less sleep later, he shares all the lows, highs and hilarious in-betweens of his experiences of first-time parenthood in this, his highly anticipated first book. Sam's honest, messy and laugh-out-loud account of trying for a baby (which transpired to be babIES) and figuring out what to do with them once they arrived - right up to the toddler years of talking, walking and tantrum-ing - will have you crying with laughter between your own nappy changes and nursery runs.

    Each mini-chapter adds one feature to the ray tracer, and by the end the reader can produce the image on the book cover. Details of basic ray tracing code architecture and C++ classes are given.

    R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you'll need to accomplish 80 percent of modern data tasks. Lander's self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You'll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you'll construct several complete models, both linear and nonlinear, and use some data mining techniques. By the time you're done, you won't just know how to write R programs, you'll be ready to tackle the statistical problems you care about most. COVERAGE INCLUDES - Exploring R, RStudio, and R packages - Using R for math: variable types, vectors, calling functions, and more - Exploiting data structures, including data.frames, matrices, and lists - Creating attractive, intuitive statistical graphics - Writing user-defined functions - Controlling program flow with if, ifelse, and complex checks - Improving program efficiency with group manipulations - Combining and reshaping multiple datasets - Manipulating strings using R's facilities and regular expressions - Creating normal, binomial, and Poisson probability distributions - Programming basic statistics: mean, standard deviation, and t-tests - Building linear, generalized linear, and nonlinear models - Assessing the quality of models and variable selection - Preventing overfitting, using the Elastic Net and Bayesian methods - Analyzing univariate and multivariate time series data - Grouping data via K-means and hierarchical clustering - Preparing reports, slideshows, and web pages with knitr - Building reusable R packages with devtools and Rcpp - Getting involved with the R global community

    This six-session study helps you see why joy is important, move into the woman God calls you to be, and find joy even in the tough times"--

    With this hands-on guide, you'll learn how to write effective, idiomatic Python code by leveraging its best and possibly most neglected features. Author Luciano Ramalho takes you through Python's core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time.Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.This book covers:Python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritanceControl flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packagesMetaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work"

    Chris Spealler is 5’5" and 140 pounds. Such daunting facts would make most declare defeat before trying. Chris didn’t buy the odds, though. Instead, he forged his own modern-day David-and-Goliath story. Speal is Chris’s account of struggle and perseverance, despite being "too small." What others did with ease, he seemed to do with sheer grit and will. And his actions put him among CrossFit’s elite. His is not a story of a gifted athlete whose natural talent granted him acclaim, but rather of one man who refused to back down and inspired an entire community in the process.

    Digital Integrated Circuits maintains a consistent, logical flow of subject matter throughout. KEY TOPICS: Addresses today's most significant and compelling industry topics, including: the impact of interconnect, design for low power, issues in timing and clocking, design methodologies, and the tremendous effect of design automation on the digital design perspective. MARKET: For readers interested in digital circuit design.

    The text is non-threatening and presents concepts clearly and succinctly with a conversational writing style. All statistical concepts are illustrated with solved applied examples immediately upon introduction. Self reviews and exercises for each section, and review sections for groups of chapters also support the student learning steps. Modern computing applications (Excel, Minitab, and MegaStat) are introduced, but the text maintains a focus on presenting statistics concepts as applied in business as opposed to technology or programming methods. The thirteenth edition continues as a students' text with increased emphasis on interpretation of data and results.

    We are bombarded with more information each day than our brains can process—especially in election season. It's raining bad data, half-truths, and even outright lies. New York Times bestselling author Daniel J. Levitin shows how to recognize misleading announcements, statistics, graphs, and written reports revealing the ways lying weasels can use them. It's becoming harder to separate the wheat from the digital chaff. How do we distinguish misinformation, pseudo-facts, distortions, and outright lies from reliable information? Levitin groups his field guide into two categories—statistical infomation and faulty arguments—ultimately showing how science is the bedrock of critical thinking. Infoliteracy means understanding that there are hierarchies of source quality and bias that variously distort our information feeds via every media channel, including social media. We may expect newspapers, bloggers, the government, and Wikipedia to be factually and logically correct, but they so often aren't. We need to think critically about the words and numbers we encounter if we want to be successful at work, at play, and in making the most of our lives. This means checking the plausibility and reasoning—not passively accepting information, repeating it, and making decisions based on it. Readers learn to avoid the extremes of passive gullibility and cynical rejection. Levitin's charming, entertaining, accessible guide can help anyone wake up to a whole lot of things that aren't so. And catch some lying weasels in their tracks!

    It covers topics ranging from personal responsibility and career development to architectural techniques for keeping your code flexible and easy to adapt and reuse. Read this book, and you'll learn how toFight software rot; Avoid the trap of duplicating knowledge; Write flexible, dynamic, and adaptable code; Avoid programming by coincidence; Bullet-proof your code with contracts, assertions, and exceptions; Capture real requirements; Test ruthlessly and effectively; Delight your users; Build teams of pragmatic programmers; and Make your developments more precise with automation. Written as a series of self-contained sections and filled with entertaining anecdotes, thoughtful examples, and interesting analogies, The Pragmatic Programmer illustrates the best practices and major pitfalls of many different aspects of software development. Whether you're a new coder, an experienced programmer, or a manager responsible for software projects, use these lessons daily, and you'll quickly see improvements in personal productivity, accuracy, and job satisfaction. You'll learn skills and develop habits and attitudes that form the foundation for long-term success in your career. You'll become a Pragmatic Programmer.

    Traditional mathematics teaching is largely about solving exactly stated problems exactly, yet life often hands us partly defined problems needing only moderately accurate solutions. This engaging book is an antidote to the rigor mortis brought on by too much mathematical rigor, teaching us how to guess answers without needing a proof or an exact calculation.In Street-Fighting Mathematics, Sanjoy Mahajan builds, sharpens, and demonstrates tools for educated guessing and down-and-dirty, opportunistic problem solving across diverse fields of knowledge--from mathematics to management. Mahajan describes six tools: dimensional analysis, easy cases, lumping, picture proofs, successive approximation, and reasoning by analogy. Illustrating each tool with numerous examples, he carefully separates the tool--the general principle--from the particular application so that the reader can most easily grasp the tool itself to use on problems of particular interest. Street-Fighting Mathematics grew out of a short course taught by the author at MIT for students ranging from first-year undergraduates to graduate students ready for careers in physics, mathematics, management, electrical engineering, computer science, and biology. They benefited from an approach that avoided rigor and taught them how to use mathematics to solve real problems.Street-Fighting Mathematics will appear in print and online under a Creative Commons Noncommercial Share Alike license.