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The Tutorials in Biostatistics have become a very popular feature of the prestigious Wiley journal, Statistics in Medicine (SIM). The introductory style and practical focus make them accessible to a wide audience including medical practitioners with limited statistical knowledge. This book represents the second of two volumes presenting the best tutorials published in SIM, focusing on statistical modeling of complex data. Topics include clustered data, hierarchical models, mixed models, genetic modeling, and meta-analysis. Each tutorial is focused on a medical problem, has been fully peer-reviewed and edited, and is authored by leading researchers in biostatistics. Many articles include an appendix on the latest developments since publication in the journal and additional references. This will appeal to statisticians working in medical research, as well as statistically-minded clinicians, biologists, epidemiologists and geneticists. It will also appeal to graduate students of biostatistics.
The Tutorials in Biostatistics have become a very popular feature of the prestigious Wiley journal, Statistics in Medicine (SIM). The introductory style and practical focus make them accessible to a wide audience including medical practitioners with limited statistical knowledge. This book represents the first of two volumes presenting the best tutorials published in SIM, focusing on statistical methods in clinical studies. Topics include the design and analysis of clinical trials, epidemiology, survival analysis, and data monitoring. Each tutorial is focused on a medical problem, has been fully peer-reviewed and edited, and is authored by leading researchers in biostatistics. Many articles include an appendix on the latest developments since publication in the journal and additional references. This will appeal to statisticians working in medical research, as well as statistically-minded clinicians, biologists, epidemiologists and geneticists. It will also appeal to graduate students of biostatistics.
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. Most methods are illustrated with specific instructions as to implementation using software either from SAS, Stata, R, Excel or Minitab. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
The ability to analyze and interpret enormous amounts of data has become a prerequisite for success in allied healthcare and the health sciences. Now in its 11th edition, Biostatistics: A Foundation for Analysis in the Health Sciences continues to offer in-depth guidance toward biostatistical concepts, techniques, and practical applications in the modern healthcare setting. Comprehensive in scope yet detailed in coverage, this text helps students understand—and appropriately use—probability distributions, sampling distributions, estimation, hypothesis testing, variance analysis, regression, correlation analysis, and other statistical tools fundamental to the science and practice of medicine. Clearly-defined pedagogical tools help students stay up-to-date on new material, and an emphasis on statistical software allows faster, more accurate calculation while putting the focus on the underlying concepts rather than the math. Students develop highly relevant skills in inferential and differential statistical techniques, equipping them with the ability to organize, summarize, and interpret large bodies of data. Suitable for both graduate and advanced undergraduate coursework, this text retains the rigor required for use as a professional reference.
Encyclopedic in breadth, yet practical and concise, Medical Biostatistics, Fourth Edition focuses on the statistical aspects ofmedicine with a medical perspective, showing the utility of biostatistics as a tool to manage many medical uncertainties. This edition includes more topics in order to fill gaps in the previous edition. Various topics have been enlarged and modified as per the new understanding of the subject.
Score your highest in biostatistics Biostatistics is a required course for students of medicine, epidemiology, forestry, agriculture, bioinformatics, and public health. In years past this course has been mainly a graduate-level requirement; however its application is growing and course offerings at the undergraduate level are exploding. Biostatistics For Dummies is an excellent resource for those taking a course, as well as for those in need of a handy reference to this complex material. Biostatisticians—analysts of biological data—are charged with finding answers to some of the world's most pressing health questions: how safe or effective are drugs hitting the market today? What causes autism? What are the risk factors for cardiovascular disease? Are those risk factors different for men and women or different ethnic groups? Biostatistics For Dummies examines these and other questions associated with the study of biostatistics. Provides plain-English explanations of techniques and clinical examples to help Serves as an excellent course supplement for those struggling with the complexities of the biostatistics Tracks to a typical, introductory biostatistics course Biostatistics For Dummies is an excellent resource for anyone looking to succeed in this difficult course.
Analyze your biostatistics data with JMP! Trevor Bihl's Biostatistics Using JMP: A Practical Guide provides a practical introduction on using JMP, the interactive statistical discovery software, to solve biostatistical problems. Providing extensive breadth, from summary statistics to neural networks, this essential volume offers a comprehensive, step-by-step guide to using JMP to handle your data. The first biostatistical book to focus on software, Biostatistics Using JMP discusses such topics as data visualization, data wrangling, data cleaning, histograms, box plots, Pareto plots, scatter plots, hypothesis tests, confidence intervals, analysis of variance, regression, curve fitting, clustering, classification, discriminant analysis, neural networks, decision trees, logistic regression, survival analysis, control charts, and metaanalysis. Written for university students, professors, those who perform biological/biomedical experiments, laboratory managers, and research scientists, Biostatistics Using JMP provides a practical approach to using JMP to solve your biostatistical problems.
The Biostatistics course is often found in the schools of public Health, medical schools, and, occasionally, in statistics and biology departments. The population of students in these courses is a diverse one, with varying preparedness. Introduction to Biostatistics assumes the reader has at least two years of high school algebra, but no previous exposure to statistics is required. Written for individuals who might be fearful of mathematics, this book minimizes the technical difficulties and emphasizes the importance of statistics in scientific investigation. An understanding of underlying design and analysis is stressed. The limitations of the research, design and analytical techniques are discussed, allowing the reader to accurately interpret results. Real data, both processed and raw, are used extensively in examples and exercises. Statistical computing packages - MINITAB, SAS and Stata - are integrated. The use of the computer and software allows a sharper focus on the concepts, letting the computer do the necessary number-crunching. - Emphasizes underlying statistical concepts more than competing texts - Focuses on experimental design and analysis, at an elementary level - Includes an introduction to linear correlation and regression - Statistics are central: probability is downplayed - Presents life tables and survival analysis - Appendix with solutions to many exercises - Special instructor's manual with solution to all exercises
Striking a balance between theory, application, and programming, Biostatistics in Public Health Using STATA is a user-friendly guide to applied statistical analysis in public health using STATA version 14. The book supplies public health practitioners and students with the opportunity to gain expertise in the application of statistics in epidemiolo
Principles and Applications of Biostatistics covers the primary concepts and methods that are required for a fundamental understanding of the use and interpretation of statistics for the biological and health sciences–from data presentation to multiple regression and analysis of variance. With a focus clarity, brevity, and accuracy, this text provides understandable and focused explanation of statistical principles and applications along with practical examples (provided in R and Microsoft Excel) and problems drawn from biological health and medical settings. Key Features: • Practical questions follow each problem to encourage students to consider why the problem likely exists, help formulate hypotheses, and then statistically assess those hypotheses. • Abundant assignment problems at the end of sections and each chapter cover a variety of application areas of biostatistics. • Rationale boxes offer explanations of why certain methods are used for specific cases.