Longer training, ever more advanced technologies—neither seems to prevent grievous errors. But in a hopeful turn, acclaimed surgeon and writer Atul Gawande finds a remedy in the humblest and simplest of techniques: the checklist. First introduced decades ago by the U.S. Air Force, checklists have enabled pilots to fly aircraft of mind-boggling sophistication. Now innovative checklists are being adopted in hospitals around the world, helping doctors and nurses respond to everything from flu epidemics to avalanches. Even in the immensely complex world of surgery, a simple ninety-second variant has cut the rate of fatalities by more than a third.In riveting stories, Gawande takes us from Austria, where an emergency checklist saved a drowning victim who had spent half an hour underwater, to Michigan, where a cleanliness checklist in intensive care units virtually eliminated a type of deadly hospital infection. He explains how checklists actually work to prompt striking and immediate improvements. And he follows the checklist revolution into fields well beyond medicine, from disaster response to investment banking, skyscraper construction, and businesses of all kinds.An intellectual adventure in which lives are lost and saved and one simple idea makes a tremendous difference, The Checklist Manifesto is essential reading for anyone working to get things right.

    But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that.This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples.By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to:- How to measure your own level of uncertainty in a conclusion or belief- Calculate Bayes theorem and understand what it's useful for- Find the posterior, likelihood, and prior to check the accuracy of your conclusions- Calculate distributions to see the range of your data- Compare hypotheses and draw reliable conclusions from themNext time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.

    Despite its relatively narrow focus, it is chock full of the pearls of clinical wisdom that students and practitioners treasure, and many of these lessons apply to medicine in general. The book was well characterized by a reviewer of an earlier edition for The New England Journal of Medicine: If only one book about surgery could be made available to physicians from all specialties, it should probably be Silen's recent revision of Cope's Early Diagnosis of the Acute Abdomen. Since the book first appeared more than 30 years ago, it has remained the classic treatise on the initial approach to abdominal pain. Because acute, severe abdominal pain is still a common problem whose misdiagnosis can result in quick death, each generation of beginning physicians is faced with the urgency of learning to make a diagnosis in this high anxiety situation and they appreciate the wise, humane, precisely detailed guidance offered by Cope and Silen. For the 21st Edition, Dr. Silen has again updated the text in a respectful but significant way. He has strengthened its emphasis on pitfalls in the interpretation of CT and ultrasound scans, on misadventures caused by over-reliance on blood tests and radiographs, and on careful history-taking to avoid the costs of inappropriate lab tests. He has also reviewed the data from a randomized clinical trial indicating that patients should receive adequate analgesia while awaiting a definitive diagnosis, a dictum that is contrary to traditional teaching

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    Thank you for your feedback and patience.From Andrew Warner:I first interviewed Paul Graham after I heard something shocking from Alexis Ohanian, a founder whose company was funded by Graham's Y Combinator. Alexis came to Mixergy to tell the story of how he launched and sold Reddit.If you're a founder, you know the kind of problems that founders have, right? Figuring out what product to create, how to build it, how to get users to try it, etc.Well Alexis didn't seem to have those problems, or at least they weren't as challenging for him as they were for most of the other 600 entrepreneurs I interviewed on Mixergy.Why? Because Paul Graham helped him launch his business.How did Graham make Reddit's launch easier and more successful than other companies' founding? How did he do the same for hundreds of other startups? And, more importantly, what can you learn from his experiences to grow your business?The book you're holding has those answers.Use what you're about to learn to build your successful startup. After you do, I hope you'll let me interview you so other founders can learn from your experience, the way you're about to benefit from Graham's.About Hyperink, the publisher:Hyperink is the easiest way for anyone to publish a beautiful, high-quality book.We work closely with subject matter experts to create each eBook. We cover topics ranging from higher education to job recruiting, from Android apps marketing to barefoot running.If you have interesting knowledge that people are willing to pay for, especially if you've already produced content on the topic, please reach out to us! There's no writing required and it's a unique opportunity to build your own brand and earn royalties.

    Readerswill find information on frequency distributions; mean, median, and mode; range, variance, and standard deviation;probability; and more.-Emphasizes Microsoft Excel for number-crunching and computationsDownload a sample chapter.

    But that's easier said than done. Many books about cognitive theory introduce radical but impractical theories, failing to make the connection to the classroom. In "Small Teaching, " James Lang presents a strategy for improving student learning with a series of modest but powerful changes that make a big difference-many of which can be put into practice in a single class period. These strategies are designed to bridge the chasm between primary research and the classroom environment in a way that can be implemented by any faculty in any discipline, and even integrated into pre-existing teaching techniques. Learn, for example: How does one become good at retrieving knowledge from memory? How does making predictions now help us learn in the future? How do instructors instill fixed or growth mindsets in their students?Each chapter introduces a basic concept in cognitive theory, explains when and how it should be employed, and provides firm examples of how the intervention has been or could be used in a variety of disciplines. Small teaching techniques include brief classroom or online learning activities, one-time interventions, and small modifications in course design or communication with students.

     Universal Methods of Design serves as an invaluable compendium of methods that can be easily referenced and used by cross-disciplinary teams in nearly any design project.   Methods and techniques are organized alphabetically for ongoing, quick reference. Each method is presented in a two-page format. The left-hand page contains a concise description of the method, accompanied by references for further reading. On the right-hand page, images and cases studies for each method are presented visually. The relevant phases for design application are highlighted as numbered icons along the right side of the page, from phases 1 (planning) through 5 (launch and monitor).Build more meaningful products with these methods and more: A/B Testing, Affinity Diagramming, Behavioral Mapping, Bodystorming, Contextual Design, Critical Incident Technique, Directed Storytelling, Flexible Modeling, Image Boards, Graffiti Walls, Heuristic Evaluation, Parallel Prototyping, Simulation Exercises, Touchstone Tours, and Weighted Matrix.  This essential guide:Dismantles the myth that user research methods are complicated, expensive, and time-consumingCreates a shared meaning for cross-disciplinary design teamsIllustrates methods with compelling visualizations and case studiesCharacterizes each method at a glanceIndicates when methods are best employed to help prioritize appropriate design research strategiesUniversal Methods of Design is an essential resource for designers of all levels and specializations.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    or House, or been absorbed by a piece in The New Yorker by Gawande, Groopman, or Nuland, or sat on that exam table wondering what's really going on in your doctor's head, then this book is for you. Expertise versus commonsense practice; moral judgments on young patients or their parents; asking tough questions; death and physician-assisted suicide; daily life with a doctor's job (yours or a family member's); doctors as patients- Klass addresses the primary issues in the life of any doctor and, by extension, the lives of those for whom they care. Perri Klass, M.D., is a writer, teacher, pediatrician, and mentor. In her frequent contributions to the New York Times, she takes on a host of issues particular to the life of a doctor-secrecy, ethics, fear, grief, and competition-with a warmth and wit her readers have come to love. Now, in the newest addition to Basic's Art of Mentoring Series, she offers her guidance, and her stories, to a new generation of doctors and readers.

    In this handy guidebook, the authors contend that you manage your boss for a very good reason: to do your best on the job—and thereby benefit not only yourself but also your supervisor and your entire company. Your boss depends on you for cooperation, reliability, and honesty. And you depend on him or her for links to the rest of the organization, for setting priorities, and for obtaining critical resources. By managing your boss—clarifying your own and your supervisor's strengths, weaknesses, goals, work styles, and needs—you cultivate a relationship based on mutual respect and understanding. The result? A healthy, productive bond that enables you both to excel. Gabarro and Kotter provide valuable guidelines for building this essential relationship—including strategies for determining how your boss prefers to process information and make decisions, tips for communicating mutual expectations, and tactics for negotiating priorities. Thought provoking and practical, Managing Your Boss enables you to lay the groundwork for one of the most crucial working relationships you'll have in your career.

    The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression.Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you're a beginner, R Cookbook will help get you started. If you're an experienced data programmer, it will jog your memory and expand your horizons. You'll get the job done faster and learn more about R in the process.Create vectors, handle variables, and perform other basic functionsInput and output dataTackle data structures such as matrices, lists, factors, and data framesWork with probability, probability distributions, and random variablesCalculate statistics and confidence intervals, and perform statistical testsCreate a variety of graphic displaysBuild statistical models with linear regressions and analysis of variance (ANOVA)Explore advanced statistical techniques, such as finding clusters in your dataWonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language--one practical example at a time.--Jeffrey Ryan, software consultant and R package author

    The better news is that by celebrating the inner strengths and uniqueness of being an "innie" THE INTROVERT ADVANTAGE shows introverts, and the extroverts who love them, how to work with instead of against their temperament to enjoy a well-lived life. Covering relationships, parenting - including parenting the introverted child - socialising, and the workplace, here are coping strategies, tactics for managing energy, and hundreds of valuable tips for not only surviving but truly thriving in an extrovert world.

    A host of specialists have contributed to the collection. This new edition includes more detailed discussion of a wider range of reference-related services including interlibrary loan, document delivery, and readers' advisory services. There is also increased attention to ethical issues and a stronger focus on user-centered services, both face-to-face and mediated by technology. In addition, the authors discuss Web sites of significant value to reference services and the impact of the Internet and World Wide Web on reference services. This carefully designed and readable text explains the essential theory and provides the practical knowledge necessary for an initial reference course. Its broad scope and organizational clarity will benefit students and practitioners.

    Written by Peter Morville, author of the groundbreaking Information Architecture for the World Wide Web, the book defines our current age as a state of unlimited findability. In other words, anyone can find anything at any time. Complete navigability.Morville discusses the Internet, GIS, and other network technologies that are coming together to make unlimited findability possible. He explores how the melding of these innovations impacts society, since Web access is now a standard requirement for successful people and businesses. But before he does that, Morville looks back at the history of wayfinding and human evolution, suggesting that our fear of being lost has driven us to create maps, charts, and now, the mobile Internet.The book's central thesis is that information literacy, information architecture, and usability are all critical components of this new world order. Hand in hand with that is the contention that only by planning and designing the best possible software, devices, and Internet, will we be able to maintain this connectivity in the future. Morville's book is highlighted with full color illustrations and rich examples that bring his prose to life.Ambient Findability doesn't preach or pretend to know all the answers. Instead, it presents research, stories, and examples in support of its novel ideas. Are we truly at a critical point in our evolution where the quality of our digital networks will dictate how we behave as a species? Is findability indeed the primary key to a successful global marketplace in the 21st century and beyond. Peter Morville takes you on a thought-provoking tour of these memes and more -- ideas that will not only fascinate but will stir your creativity in practical ways that you can apply to your work immediately.