R FOR EPIDEMIOLOGY: DISEASE SURVEILLANCE, OUTBREAK ANALYSIS, AND PUBLIC HEALTH (Decision Intelligence with R Series)

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Management number 233626566 Release Date 2026/06/27 List Price US$10.46 Model Number 233626566
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Master the power of data-driven public health with R for Epidemiology, a comprehensive and practical guide designed for students, researchers, and professionals in epidemiology, biostatistics, and health data science.In today’s rapidly evolving global health landscape, the ability to analyze disease patterns, detect outbreaks, and make evidence-based decisions is more important than ever. This book bridges the gap between epidemiological theory and real-world data analysis using the R programming language one of the most powerful tools for statistical computing and public health research.Readers are guided step-by-step through essential epidemiological concepts, including disease distribution, surveillance systems, outbreak investigation, and statistical modeling. With a strong emphasis on practical application, this book demonstrates how to use R to clean, manage, analyze, and visualize health data effectively.Inside this book, you will learn how to:Set up and use R for epidemiological analysisUnderstand and manage complex public health datasetsConduct descriptive and analytical epidemiologyBuild disease surveillance systems and detect outbreaksApply statistical models including regression and risk analysisPerform spatial epidemiology and GIS mappingAnalyze time series data and forecast disease trendsBuild complete, reproducible epidemiological projectsWhether you are analyzing infectious disease outbreaks, studying population health trends, or working in public health policy, this book provides the tools and knowledge needed to succeed.Designed for both beginners and intermediate users, R for Epidemiology combines clear explanations with practical workflows to help you gain confidence in applying R to real-world epidemiological challenges.Take your public health data analysis skills to the next level and become proficient in one of the most in-demand areas of data science today. Read more


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