Easy Interpretation Of Biostatistics E Book

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.

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.

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.

Essentials of Research Methodology and Biostatistics—A Comprehensive Guide for Health Care Professionals is a precisely written textbook for undergraduate and postgraduate medical, dental, nursing, physiotherapy, clinical psychology and other allied health care profession students. The book is an excellent attempt towards introducing the students and faculty members to the various research methodologies adopted in the field of health sciences to record health-related data. Salient Features Easy to follow: An applied, user-friendly textbook with self-explanatory simple language and presentation for the students. An example-oriented book: Plenty of examples to equip the students to prepare for exams as well as independently conduct their research activities. Illustrative presentation: Diagrammatic and tabular presentation of content to facilitate quick review and recall of important concepts. Systematic and logical organization: Content organized in systematic and logical manner to facilitate better understanding. Qualitative and quantitative research methods, analysis: Adequate coverage of quantitative as well as qualitative research process, methodology and analysis. Authentic content: Content reviewed, authenticated by a panel of renowned faculty members/experts. Unique content: Several unique topics such as sample size calculation, uses of different parametric and nonparametric statistical tests, methods, qualitative research process, and analysis included, with practical examples from Indian scenario, which are rarely found in other research methodology books. Enormous knowledge in a nutshell: In-depth coverage of all aspects of research methodology and biostatistics in a concise manner. Review questions: About 150 end-of-chapter MCQs, a useful resource for the readers to review their preparation for the university exams and also to prepare for qualifying entrance exams for postgraduate and doctoral courses.

Maintaining the same accessible and hands-on presentation, Introductory Biostatistics, Second Edition continues to provide an organized introduction to basic statistical concepts commonly applied in research across the health sciences. With plenty of real-world examples, the new edition provides a practical, modern approach to the statistical topics found in the biomedical and public health fields. Beginning with an overview of descriptive statistics in the health sciences, the book delivers topical coverage of probability models, parameter estimation, and hypothesis testing. Subsequently, the book focuses on more advanced topics with coverage of regression analysis, logistic regression, methods for count data, analysis of survival data, and designs for clinical trials. This extensive update of Introductory Biostatistics, Second Edition includes: • A new chapter on the use of higher order Analysis of Variance (ANOVA) in factorial and block designs • A new chapter on testing and inference methods for repeatedly measured outcomes including continuous, binary, and count outcomes • R incorporated throughout along with SAS®, allowing readers to replicate results from presented examples with either software • Multiple additional exercises, with partial solutions available to aid comprehension of crucial concepts • Notes on Computations sections to provide further guidance on the use of software • A related website that hosts the large data sets presented throughout the book Introductory Biostatistics, Second Edition is an excellent textbook for upper-undergraduate and graduate students in introductory biostatistics courses. The book is also an ideal reference for applied statisticians working in the fields of public health, nursing, dentistry, and medicine.

A respected introduction to biostatistics, thoroughly updated and revised The first edition of Biostatistics: A Methodology for the Health Sciences has served professionals and students alike as a leading resource for learning how to apply statistical methods to the biomedical sciences. This substantially revised Second Edition brings the book into the twenty-first century for today’s aspiring and practicing medical scientist. This versatile reference provides a wide-ranging look at basic and advanced biostatistical concepts and methods in a format calibrated to individual interests and levels of proficiency. Written with an eye toward the use of computer applications, the book examines the design of medical studies, descriptive statistics, and introductory ideas of probability theory and statistical inference; explores more advanced statistical methods; and illustrates important current uses of biostatistics. New to this edition are discussions of Longitudinal data analysis Randomized clinical trials Bayesian statistics GEE The bootstrap method Enhanced by a companion Web site providing data sets, selected problems and solutions, and examples from such current topics as HIV/AIDS, this is a thoroughly current, comprehensive introduction to the field.

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. The book 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

Medical Statistics provides the necessary statistical tools to enable researchers to undertake and understand evidence-based clinical research. It is a practical guide to conducting statistical research and interpreting statistics in the context of how the participants were recruited, how the study was designed, what types of variables were used, what effect size was found, and what the P values mean. It guides researchers through the process of selecting the correct statistics and show how to best report results for presentation and publication. Clear and concise explanations, combined with plenty of examples and tabulated explanations are based on the authors’ popular medical statistics courses. The table of contents is divided into sections according to whether data are continuous or categorical in nature as this distinction is fundamental to selecting the correct statistics. Each chapter provides a clear step-by-step guide to each statistical test with practical instructions on how to generate and interpret the numbers, and present the results as scientific tables or graphs. The chapters conclude with critical appraisal guidelines to help researchers review the reporting of results from each type of statistical test. This new edition includes a new chapter on repeated measures and mixed models and a helpful glossary of terms provides an easy reference that applies to all chapters.