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Intuitive Biostatistics

Intuitive Biostatistics Author Harvey Motulsky
ISBN-10 9780199946648
Release 2013-12-01
Pages 540
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Thoroughly revised and updated, the third edition of Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking retains and refines the core perspectives of the previous editions: a focus on how to interpret statistical results rather than on how to analyze data, minimal use of equations, and a detailed review of assumptions and common mistakes. With its engaging and conversational tone, this unique book provides a clear introduction to statistics for undergraduate and graduate students in a wide range of fields and also serves as a statistics refresher for working scientists. It is especially useful for those students in health-science related fields who have no background in biostatistics. NEW TO THIS EDITION * A new chapter on the complexities of probability * A new chapter on meta-analysis * A completely rewritten chapter on statistical traps to avoid * More sections on common mistakes in data analysis * More Q&A sections * New topics and examples * New learning tools (each chapter ends with a summary and a list of statistical terms)



Intuitive Biostatistics

Intuitive Biostatistics Author Harvey Motulsky
ISBN-10 9780199730063
Release 2010-01-01
Pages 447
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"Thoroughly revised and updated, the second edition of Intuitive Biostatistics retains and refines the core perspectives of the previous edition: a focus on how to interpret statistical results rather than on how to analyze data, minimal use of equations, and a detailed review of assumptions and common mistakes. Intuitive Biostatistics, Completely Revised Second Edition, provides a clear introduction to statistics for undergraduate and graduate students and also serves as a statistics refresher for working scientists. New to this edition: Chapter 1 shows how our intuitions lead us to misinterpret data, thus explaining the need for statistical rigor. Chapter 11 explains the lognormal distribution, an essential topic omitted from many other statistics books. Chapter 21 contrasts testing for equivalence with testing for differences. Chapters 22, 23, and 40 explore the pervasive problem of multiple comparisons. Chapters 24 and 25 review testing for normality and outliers. Chapter 35 shows how statistical hypothesis testing can be understood as comparing the fits of alternative models. Chapters 37 and 38 provide a brief introduction to multiple, logistic, and proportional hazards regression. Chapter 46 reviews one example in great depth, reviewing numerous statistical concepts and identifying common mistakes. Chapter 47 includes 49 multi-part problems, with answers fully discussed in Chapter 48. New "Q and A" sections throughout the book review key concepts"--Provided by publisher.



Intuitive Biostatistics

Intuitive Biostatistics Author Harvey Motulsky
ISBN-10 0195086074
Release 1995
Pages 386
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Designed to provide a nonmathematical introduction to biostatistics for medical and health science students, graduate students in the biological sciences, physicians, and researchers, this text explains statistical principles in non-technical language and focuses on explaining the proper scientific interpretation of statistical tests rather than on the mathematical logic of the tests themselves. Intuitive Biostatistics covers all the topics typically found in an introductory statistics text, but with the emphasis on confidence intervals rather than P values, making it easier for students to understand both. Additionally, it introduces a broad range of topics left out of most other introductory texts but used frequently in biomedical publications, including survival curves. multiple comparisons, sensitivity and specificity of lab tests, Bayesian thinking, lod scores, and logistic, proportional hazards and nonlinear regression. By emphasizing interpretation rather than calculation, this text provides a clear and virtually painless introduction to statistical principles for those students who will need to use statistics constantly in their work. In addition, its practical approach enables readers to understand the statistical results published in biological and medical journals.



Intuitive Biostatistics

Intuitive Biostatistics Author Harvey Motulsky
ISBN-10 9780199946648
Release 2013-12-01
Pages 540
Download Link Click Here

Thoroughly revised and updated, the third edition of Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking retains and refines the core perspectives of the previous editions: a focus on how to interpret statistical results rather than on how to analyze data, minimal use of equations, and a detailed review of assumptions and common mistakes. With its engaging and conversational tone, this unique book provides a clear introduction to statistics for undergraduate and graduate students in a wide range of fields and also serves as a statistics refresher for working scientists. It is especially useful for those students in health-science related fields who have no background in biostatistics. NEW TO THIS EDITION * A new chapter on the complexities of probability * A new chapter on meta-analysis * A completely rewritten chapter on statistical traps to avoid * More sections on common mistakes in data analysis * More Q&A sections * New topics and examples * New learning tools (each chapter ends with a summary and a list of statistical terms)



Fitting Models to Biological Data Using Linear and Nonlinear Regression

Fitting Models to Biological Data Using Linear and Nonlinear Regression Author Harvey Motulsky
ISBN-10 9780190291396
Release 2004-05-27
Pages 352
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Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.



Essential Biostatistics

Essential Biostatistics Author Harvey Motulsky
ISBN-10 9780199365067
Release 2015-06-25
Pages 208
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With its engaging and conversational tone, Essential Biostatistics: A Nonmathematical Approach provides a clear introduction to statistics for students in a wide range of fields, and a concise statistics refresher for scientists and professionals who need to interpret statistical results. It explains the ideas behind statistics in nonmathematical terms, offers perspectives on how to interpret published statistical results, and points out common conceptual traps to avoid. It can be used as a stand-alone text or as a supplement to a traditional statistics textbook.



Medical Statistics

Medical Statistics Author Michael J. Campbell
ISBN-10 0470976632
Release 2010-10-26
Pages 344
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Provides students and practitioners with a clear, concise introduction to the statistics they will come across in their regular reading of clinical papers. Written by three experts with wide teaching and consulting experience, Medical Statistics: A Textbook for the Health Sciences, Fourth Edition: Assumes no prior knowledge of statistics Covers all essential statistical methods Completely revised, updated and expanded Includes numerous examples and exercises on the interpretation of the statistics in papers published in medical journals From the reviews of the previous edition: "The book has several excellent features: it is written by statisticians, is.... well presented, is well referenced.... and is short." THE LANCET "Many statisticians are concerned at the generally poor standard of statistics in papers published in medical journals. Perhaps this could be remedied if more research workers would spare a few hours to read through Campbell and Machin's book." BRITISH MEDICAL JOURNAL "... a simple, interesting and insightful introduction to medical statistics... highly recommended." STATISTICAL METHODS IN MEDICAL RESEARCH "Campbell and Machin found the golden mean... this book can be recommended for all students and all medical researchers." ISCB NEWSLETTER



Designing Clinical Research

Designing Clinical Research Author Stephen B. Hulley
ISBN-10 9781469840543
Release 2013-05-08
Pages 378
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Designing Clinical Research sets the standard for providing a practical guide to planning, tabulating, formulating, and implementing clinical research, with an easy-to-read, uncomplicated presentation. This product incorporates current research methodology--including molecular and genetic clinical research--and offers an updated syllabus for conducting a clinical research workshop. Emphasis is on common sense as the main ingredient of good science. The book explains how to choose well-focused research questions and details the steps through all the elements of study design, data collection, quality assurance, and basic grant-writing.



Improving Healthcare with Control Charts

Improving Healthcare with Control Charts Author Raymond G. Carey
ISBN-10 9780873895620
Release 2003-01-01
Pages 194
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Do you feel you are drowning in a sea of data and wondering how you can learn from all of this information? While measuring quality efforts in healthcare is essential to the overall performance of any healthcare organization, it is also very complex, leaving many feeling overwhelmed and with a lot of unanswered questions: What are SPC methods and can they really help to improve healthcare? How can control charts be used to monitor key processes and outcomes? How can physicians use control charts to improve their clinical practice? In his latest book, Dr. Raymond Carey answers these questions and more as he helps to explain the need for, and the use of, SPC in healthcare. In Improving Healthcare with Control Charts: Basic and Advanced SPC Methods and Case Studies, Carey expands on his previous best-selling book, Measuring Quality Improvement in Healthcare, by providing more in-depth information on problems commonly experienced in constructing and analyzing control charts. He outlines specific SPC concepts, theories, and methods that will help improve measurement and therefore improve overall performance. Carey also presents many new case studies applying advanced methods and theory to real life healthcare situations.



Statistical Thinking for Non Statisticians in Drug Regulation

Statistical Thinking for Non Statisticians in Drug Regulation Author Richard Kay
ISBN-10 9781118470978
Release 2014-10-23
Pages 368
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Statistical Thinking for Non-Statisticians in Drug Regulation, Second Edition, is a need-to-know guide to understanding statistical methodology, statistical data and results within drug development and clinical trials. It provides non-statisticians working in the pharmaceutical and medical device industries with an accessible introduction to the knowledge they need when working with statistical information and communicating with statisticians. It covers the statistical aspects of design, conduct, analysis and presentation of data from clinical trials in drug regulation and improves the ability to read, understand and critically appraise statistical methodology in papers and reports. As such, it is directly concerned with the day-to-day practice and the regulatory requirements of drug development and clinical trials. Fully conversant with current regulatory requirements, this second edition includes five new chapters covering Bayesian statistics, adaptive designs, observational studies, methods for safety analysis and monitoring and statistics for diagnosis. Authored by a respected lecturer and consultant to the pharmaceutical industry, Statistical Thinking for Non-Statisticians in Drug Regulation is an ideal guide for physicians, clinical research scientists, managers and associates, data managers, medical writers, regulatory personnel and for all non-statisticians working and learning within the pharmaceutical industry.



Practical Statistics for Medical Research

Practical Statistics for Medical Research Author Douglas G. Altman
ISBN-10 0412276305
Release 1990-11-22
Pages 624
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Most medical researchers, whether clinical or non-clinical, receive some background in statistics as undergraduates. However, it is most often brief, a long time ago, and largely forgotten by the time it is needed. Furthermore, many introductory texts fall short of adequately explaining the underlying concepts of statistics, and often are divorced from the reality of conducting and assessing medical research. Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background. The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. The text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.



Understanding Uncertainty

Understanding Uncertainty Author Dennis V. Lindley
ISBN-10 9781118650127
Release 2013-12-16
Pages 424
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Praise for the First Edition "...a reference for everyone who is interested in knowing and handling uncertainty." —Journal of Applied Statistics The critically acclaimed First Edition of Understanding Uncertainty provided a study of uncertainty addressed to scholars in all fields, showing that uncertainty could be measured by probability, and that probability obeyed three basic rules that enabled uncertainty to be handled sensibly in everyday life. These ideas were extended to embrace the scientific method and to show how decisions, containing an uncertain element, could be rationally made. Featuring new material, the Revised Edition remains the go-to guide for uncertainty and decision making, providing further applications at an accessible level including: A critical study of transitivity, a basic concept in probability A discussion of how the failure of the financial sector to use the proper approach to uncertainty may have contributed to the recent recession A consideration of betting, showing that a bookmaker's odds are not expressions of probability Applications of the book’s thesis to statistics A demonstration that some techniques currently popular in statistics, like significance tests, may be unsound, even seriously misleading, because they violate the rules of probability Understanding Uncertainty, Revised Edition is ideal for students studying probability or statistics and for anyone interested in one of the most fascinating and vibrant fields of study in contemporary science and mathematics.



Ecology

Ecology Author William Bowman
ISBN-10 1605356182
Release 2017-03-30
Pages 598
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The new Fourth Edition of Ecology maintains its focus on providing an easy-to-read and well-organized text for instructors and students to explore the basics of ecology. This edition also continues with an increasing emphasis on enhancing student quantitative and problem solving skills. The authors also revised and strengthened key pedagogical features of Ecology, examples of which are called out from the sample pages shown. A new Hone Your Problem Solving Skills series has been added to the set of review questions at the end of each chapter. The questions expose students to hypothetical situations or existing data sets, and allow them to work through data analysis and interpretation to better understand ecological concepts. Additional Analyzing Data exercises have also been added to the existing collection on the Companion Website. These exercises enable students to enhance their essential skills sets, such as performing calculations, making graphs, designing experiments, and interpreting results.



Essential Epidemiology

Essential Epidemiology Author Penny Webb
ISBN-10 9781316684191
Release 2016-11-30
Pages
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Taking a practical approach and supported by global examples from all areas of health, the new edition of this popular and highly commended textbook has been updated to reflect current epidemiological thinking and teaching. Based on feedback from teachers and students, material has been reordered to better suit courses and reflect the underlying logic and purpose of epidemiology. • Provides students with a rounded picture of the field by emphasizing the commonalities across different areas of epidemiology, including clinical epidemiology, and highlighting the key role of epidemiology in public health • Avoids complex mathematics by restricting this to optional material, thereby keeping the book accessible to students from non-quantitative backgrounds • Integrated and supplementary questions help students to reinforce concepts • A wealth of online material is available at www.cambridge.org/essential_epidemiology, including additional questions, advanced material for key concepts, recommendations for further reading, links to useful websites and slides for teaching, supporting both students and teachers.



Fundamentals of Biostatistics

Fundamentals of Biostatistics Author Bernard Rosner
ISBN-10 9781133008170
Release 2010-08-19
Pages 888
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Bernard Rosner's FUNDAMENTALS OF BIOSTATISTICS is a practical introduction to the methods, techniques, and computation of statistics with human subjects. It prepares students for their future courses and careers by introducing the statistical methods most often used in medical literature. Rosner minimizes the amount of mathematical formulation (algebra-based) while still giving complete explanations of all the important concepts. As in previous editions, a major strength of this book is that every new concept is developed systematically through completely worked out examples from current medical research problems. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.



Statistical Methods for Survival Data Analysis

Statistical Methods for Survival Data Analysis Author Elisa T. Lee
ISBN-10 9781118593059
Release 2013-09-23
Pages 512
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Praise for the Third Edition “. . . an easy-to read introduction to survival analysis which covers the major concepts and techniques of the subject.” —Statistics in Medical Research Updated and expanded to reflect the latest developments, Statistical Methods for Survival Data Analysis, Fourth Edition continues to deliver a comprehensive introduction to the most commonly-used methods for analyzing survival data. Authored by a uniquely well-qualified author team, the Fourth Edition is a critically acclaimed guide to statistical methods with applications in clinical trials, epidemiology, areas of business, and the social sciences. The book features many real-world examples to illustrate applications within these various fields, although special consideration is given to the study of survival data in biomedical sciences. Emphasizing the latest research and providing the most up-to-date information regarding software applications in the field, Statistical Methods for Survival Data Analysis, Fourth Edition also includes: Marginal and random effect models for analyzing correlated censored or uncensored data Multiple types of two-sample and K-sample comparison analysis Updated treatment of parametric methods for regression model fitting with a new focus on accelerated failure time models Expanded coverage of the Cox proportional hazards model Exercises at the end of each chapter to deepen knowledge of the presented material Statistical Methods for Survival Data Analysis is an ideal text for upper-undergraduate and graduate-level courses on survival data analysis. The book is also an excellent resource for biomedical investigators, statisticians, and epidemiologists, as well as researchers in every field in which the analysis of survival data plays a role.



What is a P value Anyway

What is a P value Anyway Author Andrew Vickers
ISBN-10 UCSD:31822037169695
Release 2010
Pages 212
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What is a p-value Anyway? offers a fun introduction to the fundamental principles of statistics, presenting the essential concepts in thirty-four brief, enjoyable stories. Drawing on his experience as a medical researcher, Vickers blends insightful explanations and humor, with minimal math, to help readers understand and interpret the statistics they read every day. Describing data; Data distributions; Variation of study results: confidence intervals; Hypothesis testing; Regression and decision making; Some common statistical errors, and what they teach us For all readers interested in statistics.