Los mejores 30 Biostatistics libros

The Mismeasure of Man by Stephen Jay Gould explores the history of attempts to measure intelligence and the flawed assumptions and methods behind these efforts. Gould critiques the concept of biological determinism and argues against the use of IQ tests as a measure of human worth. Through engaging storytelling and meticulous analysis, the book challenges the idea that intelligence can be neatly quantified and raises important questions about the social and ethical implications of such beliefs.

Today's Health Information Management by Dana C. McWay provides a comprehensive overview of the field, covering topics such as electronic health records, data management, privacy and security, and the role of health information professionals. It offers valuable insights into the challenges and opportunities in health information management, making it a must-read for students and professionals in the healthcare industry.

Essentials of Biostatistics in Public Health provides a comprehensive introduction to biostatistics, focusing on its applications in the field of public health. Written by Lisa M. Sullivan, this book covers essential statistical concepts and methods, and their relevance to epidemiology and public health research. It is a valuable resource for students and professionals seeking to understand and utilize biostatistics in public health practice.

Fundamentals of Biostatistics by Bernard Rosner provides a comprehensive introduction to statistical concepts and methods in the field of public health and medicine. It covers topics such as study design, data analysis, and interpretation of results, making it an essential resource for students and professionals in the health sciences.

Data Manipulation with R by Phil Spector is a comprehensive guide that teaches you how to effectively manipulate and analyze data using the R programming language. From data cleaning and transformation to advanced techniques such as reshaping and merging datasets, this book equips you with the knowledge and practical skills needed to harness the power of R for data manipulation.

'Mathematica Cookbook' is a comprehensive guide written by Sal Mangano that provides a collection of practical recipes for using Mathematica, a powerful computational software. Whether you are a beginner or an experienced user, this book offers step-by-step solutions for a wide range of mathematical and scientific tasks, making it an essential resource for anyone looking to harness the full potential of Mathematica.

ggplot2 (2016) by Hadley Wickham is a comprehensive guide to creating stunning visualizations in R. The book introduces the grammar of graphics and demonstrates how to use the ggplot2 package to build custom plots layer by layer. Whether you're a beginner or an experienced data scientist, this book will help you master the art of data visualization.

Fuzzy Thinking by Bart Kosko explores the concept of fuzzy logic and how it challenges traditional binary thinking. Kosko argues that the world is not black and white, but rather filled with shades of gray, and that embracing this uncertainty can lead to better decision-making in various fields, from technology to ethics.

Getting Started with R by Andrew P. Beckerman and Dylan Z. Childs is a comprehensive guide for beginners looking to learn R programming language for statistical analysis and data visualization. The book covers the basics of R, data manipulation, visualization, and statistical modeling, making it an essential resource for anyone looking to harness the power of R for their data analysis needs.

The History of Statistics by Stephen M. Stigler is an in-depth exploration of the development and evolution of statistical methods over centuries. From its early roots in gambling and astronomy to its crucial role in shaping scientific research and public policy, this book offers a comprehensive account of how statistics has transformed our understanding of the world.

Health Care Information Systems by Karen A. Wager provides a comprehensive overview of the use of technology in healthcare. It covers topics such as electronic health records, health information exchange, and telemedicine, offering insights into how these systems can improve patient care and streamline healthcare operations. With real-world examples and case studies, this book is a valuable resource for healthcare professionals and students alike.

Regression Modeling Strategies by Frank E. Harrell Jr. provides a comprehensive guide to building and assessing predictive models using regression analysis. It offers practical advice and strategies for model development, validation, and interpretation, making it an essential resource for researchers and data analysts.

Introductory Statistics with R by Peter Dalgaard is a comprehensive guide that introduces readers to the fundamental concepts of statistics using the R programming language. It covers topics such as data visualization, probability, hypothesis testing, and regression analysis, providing clear explanations and practical examples. Whether you're a student or a professional looking to enhance your statistical skills, this book is a valuable resource for learning statistics with R.

Practical Statistics for Field Biology by Jim Fowler is a comprehensive guide that helps field biologists understand and apply statistical methods to their research. It covers a wide range of topics including data collection, analysis, and interpretation, using clear explanations and real-life examples. Whether you're studying animal behavior, ecology, or any other field biology, this book will equip you with the essential statistical skills needed for successful research.

Basic Biostatistics by B. Burt Gerstman provides a clear and comprehensive introduction to the principles and methods of biostatistics. It covers essential topics such as study design, data analysis, and interpretation of results, making it an invaluable resource for students and researchers in the field of public health and medicine.

Introduction to Probability Models by Sheldon M. Ross provides a comprehensive introduction to the theory and application of probability models. It covers a wide range of topics including random variables, Markov chains, queuing theory, and simulation. With clear explanations and numerous examples, this book is a valuable resource for students and professionals in the fields of statistics, engineering, and operations research.

Generalized Additive Models by Simon N. Wood provides a comprehensive introduction to the theory and practical application of GAMs. It covers the underlying concepts, model fitting, interpretation of results, and software implementation. This book is a valuable resource for statisticians, data analysts, and researchers interested in understanding and utilizing GAMs in their work.

Introduction to the New Statistics provides a fresh perspective on statistical methods in psychological research. Authors Geoff Cumming and Robert Calin-Jageman introduce readers to the concept of estimation, emphasizing effect sizes, confidence intervals, and meta-analysis over traditional hypothesis testing. This book revolutionizes the way statistics is taught and used in the field, promoting transparency and reproducibility in scientific studies.

Intuitive Biostatistics by Harvey Motulsky is a comprehensive guide to understanding and applying statistical concepts in the field of biostatistics. It offers clear explanations and real-world examples to help readers grasp complex statistical methods and their relevance to medical and biological research. Whether you're a student, researcher, or healthcare professional, this book will enhance your ability to interpret and critically evaluate scientific data.

Essentials of Writing Biomedical Research Papers by Mimi Zeiger provides a comprehensive guide to writing and publishing scientific research papers in the biomedical field. It covers essential topics such as structuring a paper, presenting data, citing sources, and adhering to journal guidelines. Whether you're a student, researcher, or aspiring author, this book offers valuable insights and practical tips to improve your writing skills in the field of biomedical research.

Modern Statistics for Modern Biology by Wolfgang Huber and Susan Holmes offers a comprehensive guide to statistical analysis in the field of biology. The book covers a wide range of topics including experimental design, hypothesis testing, regression analysis, and statistical programming in R. It provides practical examples and exercises to help biologists apply statistical methods to their own research.

The Visual Display of Quantitative Information (1983) by Edward R. Tufte is a groundbreaking book that explores the design and presentation of statistical data. Tufte discusses principles for displaying complex information in a way that is clear, accurate, and visually appealing. Through numerous examples and illustrations, the book challenges traditional methods of data visualization and offers innovative techniques for conveying data effectively.

The Cartoon Guide to Statistics by Larry Gonick and Woollcott Smith is a fun and informative book that uses cartoons and witty dialogue to explain the key concepts of statistics. It covers a wide range of topics including probability, correlation, regression analysis, and more. Whether you're a student struggling with statistics or just someone who wants to understand the world of data better, this book makes learning statistics enjoyable and easy to grasp.

Introduction to Meta-Analysis by Michael Borenstein and Larry V. Hedges is a comprehensive guide to the principles and techniques of meta-analysis. This book provides a clear and easy-to-understand introduction to the statistical methods used in combining and analyzing data from multiple studies. It is a valuable resource for researchers and students looking to understand and conduct meta-analyses in various fields of study.

Getting Started with R provides a comprehensive introduction to the R programming language, designed for beginners. It covers the basics of R, data manipulation, visualization, and statistical analysis. With clear explanations and practical examples, this book is a great resource for anyone looking to learn R for data analysis.

Introduction to the New Statistics by Geoff Cumming offers a fresh perspective on statistical analysis. It introduces the concept of effect sizes and confidence intervals, challenging the traditional reliance on p-values. This book provides a comprehensive guide for researchers and students looking to embrace a more informative and transparent approach to data analysis.

Introduction to Meta-Analysis provides a comprehensive overview of the principles and methods of meta-analysis in research. Written by Michael Borenstein and his co-authors, this book covers the fundamental concepts, statistical techniques, and practical considerations involved in conducting a meta-analysis. It serves as a valuable resource for researchers, students, and professionals looking to synthesize and interpret findings from multiple studies.

Mathematica Cookbook by Salvatore Mangano offers a collection of practical recipes for using Mathematica, a powerful computational software. Whether you're a beginner or an experienced user, this book provides step-by-step instructions and examples to help you solve complex mathematical problems, visualize data, and create interactive applications. It's a valuable resource for anyone looking to harness the full potential of Mathematica.

Modern Statistics for Modern Biology by Susan Holmes is a comprehensive guide that introduces biologists to the essential statistical techniques and computational tools needed for analyzing and interpreting biological data. The book covers topics such as data visualization, hypothesis testing, regression analysis, and machine learning, all with a focus on real-world biological applications. It provides clear explanations and practical examples, making it an invaluable resource for biologists looking to enhance their statistical skills.

The Cartoon Guide to Statistics by Larry Gonick is a fun and engaging book that simplifies the complex world of statistics through humorous illustrations and easy-to-understand explanations. Whether you're a student struggling with stats or just someone who wants to grasp the basics, this book will make the subject more accessible and enjoyable.