Susan Macqueen was 12 years old when she accompanied her mother to see her friend Ms. Fairweather, the matron at the local nursing home, and from that day on she knew she wanted to be a nurse. A few years later, despite being told that her grades weren't good enough, Susan was accepted on the three-year nurses training course at Addenbooke's hospital in Cambridge. It wasn't long before Susan knew she wanted to work with children and set her sights on a job at Great Ormond Street. Thirty-five years later, on her third attempt, Susan has finally retired from that iconic hospital and is enjoying a more leisurely pace of life. Hope, despair, laughter, and tears, Susan's stories move the reader through the incredible stories that she was faced with on an every day basis.

    This manual provides that evidence, based on an appraisal of current research and advice from clinical experts.New for the seventh edition:A new chapter on 'Positioning' - how to help a patient sit in bed, to stand and lie comfortablySeparate chapters on 'Assessment and the process of care' and 'Communication'New sections on problem solving, to help nurses during the course of their clinical workEvidence rated to help nurses assess its validity This invaluable companion enables nurses to gain the confidence they need to become informed, skilled practitioners.Now available online to Hospitals, NHS Trusts and Academic Institutions

    Most people say they would like to die quietly at home. But overly aggressive medical advice, coupled with an unrealistic sense of invincibility or overconfidence in our health-care system, results in the majority of elderly patients misguidedly dying in institutions. Many undergo painful procedures instead of having the better and more peaceful death they deserve.At Peace outlines specific active and passive steps that older patients and their health-care proxies can take to ensure loved ones live their last days comfortably at home and/or in hospice when further aggressive care is inappropriate. Through Dr. Samuel Harrington's own experience with the aging and deaths of his parents and of working with patients, he describes the terminal patterns of the six most common chronic diseases; how to recognize a terminal diagnosis even when the doctor is not clear about it; how to have the hard conversation about end-of-life wishes; how to minimize painful treatments; when to seek hospice care; and how to deal with dementia and other special issues. Informed by more than thirty years of clinical practice, Dr. Harrington came to understand that the American health-care system wasn't designed to treat the aging population with care and compassion. His work as a hospice trustee and later as a hospital trustee drove his passion for helping patients make appropriate end-of-life decisions.

    Afrin started coming to understand that a newly recognized type of mast cell disease, now called mast cell activation syndrome (MCAS), was the underlying diagnosis in many patients he was seeing who were each suffering large assortments — quite different from one patient to the next — of chronic multisystem inflammatory illnesses of unclear cause. Dr. Afrin soon gained experience that MCAS is far more prevalent than the only mast cell disease previously known to medicine (the rare disease of mastocytosis) and that most MCAS patients, once accurately diagnosed, can eventually find significantly helpful medications targeted at the disease. The frequency and magnitude of the improvements Dr. Afrin has seen — even the relief that comes from finally having a unifying diagnosis other than "psychosomatism" — have spurred him to focus in this area, not only tending to the needs of his patients but also pursuing research to advance our understanding of the disease and helping to educate other professionals who in turn can help even more of the many people who have long been suffering not only the symptoms of the disease but also the natural concern of not understanding why one would be so "unlucky" to have acquired so many medical problems. As it turns out, such patients are not so unlucky and truly have just one root issue (and a very common one at that), which has the biological capability to develop, directly or indirectly, into most or all of their previously diagnosed problems. There is a great deal yet to learn about this, but even with just the present very limited understanding, the opportunity to diagnose and help patients with MCAS seems to be enormous and Dr. Afrin felt a description of the disease, written for the general public, might help lead some MCAS patients on a journey to diagnosis and improvement sooner rather than later. Dr. Afrin hopes this book will help people who might have, or do have, MCAS. A portion of the proceeds of purchases of this book will go to support research and education in this area.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    Polya, How to Solve It will show anyone in any field how to think straight. In lucid and appealing prose, Polya reveals how the mathematical method of demonstrating a proof or finding an unknown can be of help in attacking any problem that can be reasoned out--from building a bridge to winning a game of anagrams. Generations of readers have relished Polya's deft--indeed, brilliant--instructions on stripping away irrelevancies and going straight to the heart of the problem.

    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.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    Each self-contained chapter consists of three sections. The first describes the statistic, including how it is used and what information it provides. The second section reviews how it works, how to calculate the formula, the strengths and weaknesses of the technique, and the conditions needed for its use. The final section provides examples that use and interpret the statistic. A glossary of terms and symbols is also included.New features in the second edition include:an interactive CD with PowerPoint presentations and problems for each chapter including an overview of the problem's solution; new chapters on basic research concepts including sampling, definitions of different types of variables, and basic research designs and one on nonparametric statistics; more graphs and more precise descriptions of each statistic; and a discussion of confidence intervals.This brief paperback is an ideal supplement for statistics, research methods, courses that use statistics, or as a reference tool to refresh one's memory about key concepts. The actual research examples are from psychology, education, and other social and behavioral sciences.Materials formerly available with this book on CD-ROM are now available for download from our website www.psypress.com. Go to the book's page and look for the 'Download' link in the right-hand column.

    Perfect for fans of When Breath Becomes Air.In 1990, Robert K. Brown was an ordinary college student studying abroad in England when a series of unexpected and extraordinary events would change the trajectory of his life forever. Choosing to ignore ominous early symptoms, he was still troubled enough to write in his journal "just for the record ... I am frightened because things are happening to me that I can’t explain away."What follows is a race against time to return home to Seattle for months of chemotherapy, countless complications, and a search for as much normalcy as possible when you're forced to face your mortality at twenty."While memoirs of surviving disease are plenty, Hundred Percent Chance stands apart through its genuine humor and unflinching portrayal of both the physical and psychological struggles that accompany a diagnosis of disease. Brown avoids inspirational platitudes, instead demonstrating the need for perspective and perseverance in the face of illness."Every person Brown introduces, whether their role is significant or small, will leave a memorable impression on readers. This memoir's focus on the tiny moments that ultimately shape and define a life, are particularly poignant and engrossing" (The BookLife Prize).10% of all proceeds will benefit The Leukemia & Lymphoma Society.

    Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays. This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.

    I’m afraid…As death approaches, both patient and family must cope with grief, pain, and seemingly unanswerable questions. It’s a time of challenge, of concerns. But, as hospice nurse Karen Whitley Bell reminds us, it also offers an opportunity to explore and rediscover the fuller, richer meaning of life.Drawing on her years of experience, Bell has created a comprehensive, insightful guide to every aspect of hospice care and the final stages of life. She discusses the physical, emotional, and spiritual journey a dying person goes through; care-giving during this difficult period; closure, and loss and the lessons it teaches us. In addition to her warm, yet knowledgeable voice, readers get firsthand accounts of experiences in hospice care, making Living at the End of Life accessible, reassuring, and indispensable.

    Conflict between humans and machines is seen as inevitable and its outcome all too predictable.In this groundbreaking book, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines. He describes the near-term benefits we can expect, from intelligent personal assistants to vastly accelerated scientific research, and outlines the AI breakthroughs that still have to happen before we reach superhuman AI. He also spells out the ways humans are already finding to misuse AI, from lethal autonomous weapons to viral sabotage.If the predicted breakthroughs occur and superhuman AI emerges, we will have created entities far more powerful than ourselves. How can we ensure they never, ever, have power over us? Russell suggests that we can rebuild AI on a new foundation, according to which machines are designed to be inherently uncertain about the human preferences they are required to satisfy. Such machines would be humble, altruistic, and committed to pursue our objectives, not theirs. This new foundation would allow us to create machines that are provably deferential and provably beneficial.In a 2014 editorial co-authored with Stephen Hawking, Russell wrote, "Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last." Solving the problem of control over AI is not just possible; it is the key that unlocks a future of unlimited promise.

    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

    You may have tried and failed in the past to make running stick, but never the less you are determined to master it. You may tell yourself that “running is hard”, or “I’m just not a runner”, but the truth is that anybody can learn to run if they have the right approach. You will likely have many questions; “how do I build up my running distance?”, “how do I stay motivated to run?”, “how do I warm up and cool down?”. All of these and more are covered off within the pages of this book along with a step by step guide to building up your running to 60 minutes. There is more to learning how to run than just going out and seeing how far you can go three days a week. Some people will undoubtedly have success with this method, but for most beginner runners it takes a little more guidance and support to truly master the art of running. More and more beginners are deciding to take their first steps and learn how to run. Races are popping up all over the place geared towards beginner runners and it remains one of the most accessible sports around. Learning how to run should be a fun and rewarding experience in itself, not just a means to achieve a goal. Beginner’s Luck is a complete program that teaches you everything you need to build your confidence as a runner. The program itself removes the pressure of having to stick rigidly to a set rate of progress, and instead allows you to progress at your own pace. If you are a beginner runner who would like to learn how to run for up to an hour AND surprise yourself as to how easy it really is, get Beginner’s Luck and start out on your journey today.