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.

    Successfully defended in 1969 as Deleuze's main thesis toward his Doctorat d'Etat at the Sorbonne, the work has been central in initiating the shift in French thought away from Hegel and Marx, towards Nietzsche and Freud. The text follows the development of two central concepts, those of pure difference and complex repetition. It shows how the two concepts are related - difference implying divergence and decentering, and repetition implying displacement and disguising. In its explication the work moves deftly between Hegel, Kierkegaard, Freud, Althusser, and Nietzsche to establish a fundamental critique of Western metaphysics. Difference and Repetition has become essential to the work of literary critics and philosophers alike, and this translation his been long awaited.

    This claim is not only false, but its presence in the debate is an insult to science." With these words, the authors begin a detailed analysis of one of the most controversial topics of the day. The authors make a compelling case against claims of a scientific consensus. The purported proof of such a consensus consists of sloppy research by nonscientists, college students, and a highly partisan Australian blogger. Surveys of climate scientists, even those heavily biased in favor of climate alarmism, find extensive disagreement on the underlying science and doubts about its reliability. The authors point to four reasons why scientists disagree about global warming: a conflict among scientists in different and often competing disciplines; fundamental scientific uncertainties concerning how the global climate responds to the human presence; failure of the United Nations Intergovernmental Panel on Climate Change (IPCC) to provide objective guidance to the complex science; and bias among researchers. The authors offer a succinct summary of the real science of climate change based on their previously published comprehensive review of climate science in a volume titled Climate Change Reconsidered II: Physical Science. They recommend that policymakers resist pressure from lobby groups to silence scientists who question the authority of the IPCC to claim to speak for climate science. More than 50,000 copies of the first edition were sold or given away in five months to elected officials, civic and business leaders, scientists, and other opinion leaders. The response from the science community and experts on climate change has been overwhelmingly positive. To meet demand for more copies, we have produced this second revised edition. Changes include a foreword by Marita Noon, at the time executive director of Energy Makes America Great, Inc. Some of the discussion in Chapter 1 has been revised and expanded thanks to feedback from readers of the first edition. Graphs in Chapters 4, 5, and 6 are now full color, and new graphs have been added.

    In addition, it should have repercussions in a variety of disciplines, ranging from anthropology and psychology to epistemology and the philosophy of science. . . . Lakoff asks: What do categories of language and thought reveal about the human mind? Offering both general theory and minute details, Lakoff shows that categories reveal a great deal."—David E. Leary, American Scientist

    R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. * Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. * Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. * The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. * Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. * Includes numerous worked examples and exercises within each chapter. * Accompanied by a website featuring worked examples, data sets, exercises and solutions: http: //www.imperial.ac.uk/bio/research/crawl... Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.

    Designed primarily for undergraduates, this self-help manual offers straightforward solutions to common problems and an overview of the diversity of writing tasks faced by professional biologists.

    His aim is to present calculus as the first real encounter with mathematics: it is the place to learn how logical reasoning combined with fundamental concepts can be developed into a rigorous mathematical theory rather than a bunch of tools and techniques learned by rote. Since analysis is a subject students traditionally find difficult to grasp, Spivak provides leisurely explanations, a profusion of examples, a wide range of exercises and plenty of illustrations in an easy-going approach that enlightens difficult concepts and rewards effort. Calculus will continue to be regarded as a modern classic, ideal for honours students and mathematics majors, who seek an alternative to doorstop textbooks on calculus, and the more formidable introductions to real analysis.

    The only reference text to identify the top resources in major subject areas and genres, it shows students how to approach the reference query by matching specific types of questions to the most appropriate format (when answering questions that require handy facts, for example, go first to ready reference sources; for questions about current events and issues, start with indexes). The book begins with the essentials -- interviewing patrons, determining the information need, and developing a basic search strategy. It then gives a thorough overview of the materials, print and electronic, most frequently used to answer questions -- from government information to bibliographic resources, dictionaries, encyclopedias, biographical information sources, atlases, and more. A section on special topics in reference includes chapters on when and how to use the Internet as a reference tool, suggestions on user instruction at the reference desk, and reader's advisory work, as well as a chapter on service to children and youth authored by acclaimed expert Mary K. Chelton. Finally, the book addresses reference management basics: selection and evaluation of material, management of the reference department, assessing and improving reference services, and future trends. Guided by an advisory board and a focus group, the authors have achieved an ideal balance between practical elements and guiding principles. This landmark text is sure to be of interest to LIS educators, students, and both novice and experienced reference professionals.

    Full of insights, arguments and philosophical perspectives, the book covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory, computability and complexity theory, quantum computing, cryptography, the information content of quantum states and the interpretation of quantum mechanics. There are also extended discussions about time travel, Newcomb's Paradox, the anthropic principle and the views of Roger Penrose. Aaronson's informal style makes this fascinating book accessible to readers with scientific backgrounds, as well as students and researchers working in physics, computer science, mathematics and philosophy.

    Henry Bergson (1859-1941) was awarded the Nobel Prize in 1927. His works include Time & Free Will, An Introduction to Metaphysics, Creative Evolution & The Creative Mind.

    With it you can prime yourself with the key concepts of statistics before getting involved in the associated calculations. Using words and diagrams instead of figures, formulae and equations, Derek Rowntree makes statistics accessible to those who are non-mathematicians. And just to get you into the spirit of things. Rowntree has included questions in his argument; answer them as you go and you will be able to tell how far you have mastered the subject.

    This is not the same as “doing math.” The latter usually involves the application of formulas, procedures, and symbolic manipulations; mathematical thinking is a powerful way of thinking about things in the world -- logically, analytically, quantitatively, and with precision. It is not a natural way of thinking, but it can be learned. Mathematicians, scientists, and engineers need to “do math,” and it takes many years of college-level education to learn all that is required. Mathematical thinking is valuable to everyone, and can be mastered in about six weeks by anyone who has completed high school mathematics. Mathematical thinking does not have to be about mathematics at all, but parts of mathematics provide the ideal target domain to learn how to think that way, and that is the approach taken by this short but valuable book. The book is written primarily for first and second year students of science, technology, engineering, and mathematics (STEM) at colleges and universities, and for high school students intending to study a STEM subject at university. Many students encounter difficulty going from high school math to college-level mathematics. Even if they did well at math in school, most are knocked off course for a while by the shift in emphasis, from the K-12 focus on mastering procedures to the “mathematical thinking” characteristic of much university mathematics. Though the majority survive the transition, many do not. To help them make the shift, colleges and universities often have a “transition course.” This book could serve as a textbook or a supplementary source for such a course. Because of the widespread applicability of mathematical thinking, however, the book has been kept short and written in an engaging style, to make it accessible to anyone who seeks to extend and improve their analytic thinking skills. Going beyond a basic grasp of analytic thinking that everyone can benefit from, the STEM student who truly masters mathematical thinking will find that college-level mathematics goes from being confusing, frustrating, and at times seemingly impossible, to making sense and being hard but doable. Dr. Keith Devlin is a professional mathematician at Stanford University and the author of 31 previous books and over 80 research papers. His books have earned him many awards, including the Pythagoras Prize, the Carl Sagan Award, and the Joint Policy Board for Mathematics Communications Award. He is known to millions of NPR listeners as “the Math Guy” on Weekend Edition with Scott Simon. He writes a popular monthly blog “Devlin’s Angle” for the Mathematical Association of America, another blog under the name “profkeithdevlin”, and also blogs on various topics for the Huffington Post.

    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

    It is ideal as a reader for all courses in epistemology.

    Topics include: Trigonometric Identities & Equations, Circular Functions, and Polar Equations & Complex Numbers.