Understanding Biostatistics looks at the fundamentals of biostatistics, using elementary statistics to explore the nature of statistical tests. This book is intended to complement first-year statistics and biostatistics textbooks. The main focus here is on ideas, rather than on methodological details. Basic concepts are illustrated with representations from history, followed by technical discussions on what different statistical methods really mean. Graphics are used extensively throughout the book in order to introduce mathematical formulae in an accessible way. Key features: Discusses confidence intervals and p-values in terms of confidence functions. Explains basic statistical methodology represented in terms of graphics rather than mathematical formulae, whilst highlighting the mathematical basis of biostatistics. Looks at problems of estimating parameters in statistical models and looks at the similarities between different models. Provides an extensive discussion on the position of statistics within the medical scientific process. Discusses distribution functions, including the Guassian distribution and its importance in biostatistics. This book will be useful for biostatisticians with little mathematical background as well as those who want to understand the connections in biostatistics and mathematical issues.

Learn biostatistics the easy way. This outstanding resource presents the key concepts you need to understand biostatistics and how to apply them in clinical medicine. Easy-to-understand examples and analogies explain complex concepts, and practical applications provide you with real tools for use in daily practice. The book's organization is intuitive, so that concepts build upon one another, maximizing understanding. This book will give you the confidence to appraise the existing literature - and the vocabulary you need to discuss it. - Uses an easy-to-understand presentation and writing style to make the material easily accessible. - Places its emphasis on concepts, not formulas, for more clinical-based guidance. - Focuses on practical applications of biostatistics to medical practice to give you a better understanding of how and why research is conducted. - Presents concise but comprehensive coverage to create easily accessible yet complete information. - Provides examples, analogies, and memorization tips to make the material easier to absorb.

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.

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.

Anyone who attempts to read genetics or epidemiology research literature needs to understand the essentials of biostatistics. This book, a revised new edition of the successful Essentials of Biostatistics has been written to provide such an understanding to those who have little or no statistical background and who need to keep abreast of new findings in this fast moving field. Unlike many other elementary books on biostatistics, the main focus of this book is to explain basic concepts needed to understand statistical procedures. This Book: Surveys basic statistical methods used in the genetics and epidemiology literature, including maximum likelihood and least squares. Introduces methods, such as permutation testing and bootstrapping, that are becoming more widely used in both genetic and epidemiological research. Is illustrated throughout with simple examples to clarify the statistical methodology. Explains Bayes’ theorem pictorially. Features exercises, with answers to alternate questions, enabling use as a course text. Written at an elementary mathematical level so that readers with high school mathematics will find the content accessible. Graduate students studying genetic epidemiology, researchers and practitioners from genetics, epidemiology, biology, medical research and statistics will find this an invaluable introduction to statistics.

This book introduces and discusses the most important aspects of clinical research methods and biostatistics for oncologists, pursuing a tailor-made and practical approach. Evidence-based medicine (EBM) has been in vogue in the last few decades, particularly in rapidly advancing fields such as oncology. This approach has been used to support decision-making processes worldwide, sparking new clinical research and guidelines on clinical and surgical oncology. Clinical oncology research has many peculiarities, including specific study endpoints, a special focus on survival analyses, and a unique perspective on EBM. However, during medical studies and in general practice, these topics are barely taught. Moreover, even when EBM and clinical cancer research are discussed, they are presented in a theoretical fashion, mostly focused on formulas and numbers, rather than on clinical application for a proper literature appraisal. Addressing that gap, this book discusses more practical aspects of clinical research and biostatistics in oncology, instead of relying only on mathematical formulas and theoretical considerations. Methods and Biostatistics in Oncology will help readers develop the skills they need to understand the use of research on everyday oncology clinical practice for study design and interpretation, as well to demystify the use of EBM in oncology.