Principles And Applications Of Biostatistics

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.

Principles and Practice of Biostatistics emphasizes the basic aspects of biostatistics most often used in the teaching and research areas of medical, nursing and allied health sciences. Written in a simple tone and chapters are organized in logical order to ease the process of understanding. Covers topics such as basic biostatistics, epidemiology & clinical trials, research methods & data management, and the most commonly used regression methods. Stresses on the importance and appropriateness of statistical methods, their assumptions, validity and interpretation in the context of clinical data. Each chapter is organized into Learning Objectives, Introduction of various statistical methods illustrated with Worked Examples and graphical methods as appropriate, ending with summarized Key Points. Review Questions, Exercises and Multiple Choice Questions enable the reader a quick grasp of and greater insight into the methods presented in the text.

This introduction to biostatistics offers health science studentsQwith limited math and statistics backgroundsQa conceptually-based introduction to statistical procedures that will prepare them to conduct or evaluate research in biological and health sciences. Enthusiasm for the material will quickly spread to the reader from the author. The author's appealing writing style makes users of the text Rforget it is math.S Students are encouraged to use common sense rather than rigorous theory to gain an understanding of statistics..The authors rely heavily on graphics to illustrate material and incorporate the use of computers to facilitate doing computations so students can concentrate on concepts. Quantitative principles discussed include descriptive statistics, life tables, probability, hypothesis testing, parameter estimation, regression (linear and logistic) correlation, survival analysis, analysis of variance, and more.

This conceptually-based introduction to statistical procedures prepares public health and life sciences students to conduct and evaluate research in the biological and public health sciences. The authors illustrate that statistics is more than just maths - it's a viable field that has hundreds of applications and uses in the real world. The authors rely heavily on the book's graphics and the use of computers to help students make the calculations, giving them more time to concentrate on and learn the concepts.

Here is a book for clinicians, clinical investigators, trainees, and graduates who wish to develop their proficiency in the planning, execution, and interpretation of clinical and epidemiological research. Emphasis is placed on the design and analysis of research studies involving human subjects where the primary interest concerns principles of analytic (cause-and- effect) inference. The topic is presented from the standpoint of the clinician and assumes no previous knowledge of epidemiology, research design or statistics. Extensive use is made of illustrative examples from a variety of clinical specialties and subspecialties. The book is divided into three parts. Part I deals with epidemiological research design and analytic inference, including such issues as measurement, rates, analytic bias, and the main forms of observational and experimental epidemiological studies. Part II presents the principles and applications of biostatistics, with emphasis on statistical inference. Part III comprises four chapters covering such topics as diagnostic tests, decision analysis, survival (life-table) analysis, and causality.

This book offers a comprehensive guide to essential techniques and methods in biostatistics, addressing the underlying concepts to aid in comprehension. The use of biostatistics techniques has increased manifold in the recent past, due to their suitability for applications in a wide range of problems in various fields. This book helps learners grasp the materials in detail, equipping them to use biostatistics techniques independently and confidently. The book starts with a summary of background materials, followed by methods and techniques. As such, with only minimum guidance from teachers, this book can provide materials for self-learning of biostatistics techniques with a deeper level of understanding. The first two chapters focus on fundamental concepts, sources of data, data types, organization of data, and descriptive statistics, followed by the basic probability concepts, distributions and sampling distributions needed in order to combine descriptive statistics with inferential techniques. Estimation and tests of hypotheses are illustrated in two separate chapters. Important measures of association, linear regression, analysis of variance and logistic regression, and proportional hazards models are then presented systematically, ensuring that the book covers the topics most essential to students and users of biostatistics in connection with a wide range of applications in various fields. The book has been carefully structured, and the content is presented in a sequence covering the essential background in a highly systematic manner, supporting the learning process by presenting theory and applications that complement one another.

This edition is a reprint of the second edition published in 2000 by Brooks/Cole and then Cengage Learning. Principles of Biostatistics is aimed at students in the biological and health sciences who wish to learn modern research methods. It is based on a required course offered at the Harvard School of Public Health. In addition to these graduate students, many health professionals from the Harvard medical area attend as well. The book is divided into three parts. The first five chapters deal with collections of numbers and ways in which to summarize, explore, and explain them. The next two chapters focus on probability and introduce the tools needed for the subsequent investigation of uncertainty. It is only in the eighth chapter and thereafter that the authors distinguish between populations and samples and begin to investigate the inherent variability introduced by sampling, thus progressing to inference. Postponing the slightly more difficult concepts until a solid foundation has been established makes it easier for the reader to comprehend them. All supplements, including a manual for students with solutions for odd-numbered exercises, a manual for instructors with solutions to all exercises, and selected data sets, are available at http://www.crcpress.com/9781138593145.