How to Read a Paper: The Basics of Evidence-based Medicine and Healthcare (7版)

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【簡介】 重量：0.51kg 頁數： 328 裝訂：平裝　開數：21.6 x 14 cm 印刷:雙色 Learn to assess published research in this best-selling introduction to evidence-based healthcare Evidence-based practices have revolutionized medical care. Clinical and scientific papers have something to offer practitioners at every level of the profession, from students to established clinicians in medicine, nursing and allied professions. Novices are often intimidated by the idea of reading and appraising the research literature. How to Read a Paper demystifies this process with a thorough, engaging introduction to how clinical research papers are constructed and how to evaluate them. Now fully updated to incorporate new areas of research, readers of the seventh edition of How to Read a Paper will also find: A careful balance between the principles of evidence-based healthcare and clinical practice New chapters covering consensus methods, mechanistic evidence, big data and artificial intelligence Detailed coverage of subjects like assessing methodological quality, systemic reviews and meta-analyses, qualitative research, and more. How to Read a Paper is ideal for all healthcare students and professionals seeking an accessible introduction to evidence-based healthcare – particularly those sitting undergraduate and postgraduate exams and preparing for interviews.

Introduction to the Basics of Real Analysis

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Contents: Sets and Functions Real Number System Basics of Real Analysis Sequences of Real Numbers Limits and Continuity Uniform Continuity of Real Functions Differentiability of Real Functions Uniform Convergence of Sequences and Series of Real Functions Functions of Several Variables Riemann Integration The Improper Integrals Metric Spaces

Miller's Basics of Anesthesia (8版)

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Basics of Statistical Physics (3版)

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Statistics links microscopic and macroscopic phenomena, and requires for this reason a large number of microscopic elements like atoms. The results are values of maximum probability or of averaging. This introduction to statistical physics concentrates on the basic principles and attempts to explain these in simple terms, supplemented by numerous examples. These basic principles include the difference between classical and quantum statistics, a priori probabilities as related to degeneracies, the vital aspect of indistinguishability as compared with distinguishability in classical physics, the differences between conserved and non-conserved elements, the different ways of counting arrangements in the three statistics (Maxwell–Boltzmann, Fermi–Dirac, Bose–Einstein), the difference between maximization of the number of arrangements of elements, and averaging in the Darwin–Fowler method. Significant applications to solids, radiation and electrons in metals are treated in separate chapters, as well as Bose–Einstein condensation. In this latest edition, apart from a general revision, the topic of thermal radiation has been expanded with a new section on black bodies and an additional chapter on black holes. Other additions are more examples with applications of statistical mechanics in solid state physics and superconductivity. Throughout the presentation, the introduction carries almost all details for calculations. Request Inspection Copy Sample Chapter(s) Preface to Third Edition, Second Edition and First Edition Chapter 1: Introduction Contents: Introduction Statistical Mechanics of an Ideal Gas (Maxwell) The a priori Probability Classical Statistics (Maxwell–Boltzmann) Entropy Quantum Statistics Exact Form of Distribution Functions Application to Radiation (Light Quanta) Debye Theory of Specific Heat of Solids Electrons in Metals Limitations of the Preceding Theory — Improvement with Ensemble Method Averaging instead of Maximization, and Bose–Einstein Condensation The Boltzmann Transport Equation Thermal Radiation of Black Holes Readership: Advanced undergraduates, graduate students and academics interested in statistical physics.