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Introduction to Data Science in Biostatistics Using R, the Tidyverse Ecosystem, and APIs - Thomas W. MacFarland 2024 PDF Springer BOOKS
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Introduction to Data Science in Biostatistics Using R, the Tidyverse Ecosystem, and APIs
Author: Thomas W. MacFarland
Year: 2024
Pages: 536
Format: PDF
File size: 21.5 MB
Language: ENG



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Book Description: 'Introduction to Data Science in Biostatistics Using R the Tidyverse Ecosystem and APIs' is a comprehensive guide that provides a thorough introduction to data science in biostatistics using R and the tidyverse ecosystem. The book covers the fundamentals of R programming, data visualization, and statistical analysis, as well as the use of APIs to obtain and analyze data from various sources. It also explores the application of machine learning techniques to solve real-world problems in healthcare, medicine, and public health. The book is divided into four parts: Part I: Fundamentals of R Programming and Data Visualization; Part II: Statistical Analysis; Part III: Machine Learning Techniques; and Part IV: Real-World Applications. Each part includes practical exercises to help readers apply their knowledge and gain hands-on experience. The book begins by introducing the basics of R programming and data visualization, emphasizing the importance of understanding the process of technology evolution and developing a personal paradigm for perceiving the technological process of developing modern knowledge. The author argues that this perspective is essential for survival in a rapidly changing world and for the unification of people in a warring state.
«Introduction to Data Science in Biostatistics Using R the Tidyverse Ecosystem and APIs» - это всеобъемлющее руководство, которое содержит подробное введение в науку о данных в биостатистике с использованием R и экосистемы tidyverse. Книга охватывает основы программирования R, визуализации данных и статистического анализа, а также использование API для получения и анализа данных из различных источников. В нем также исследуется применение методов машинного обучения для решения реальных проблем в здравоохранении, медицине и здравоохранении. Книга разделена на четыре части: Часть I: Основы программирования R и визуализации данных; Часть II: Статистический анализ; Часть III: Техника машинного обучения; и Часть IV: Реальные приложения. Каждая часть включает практические занятия, которые помогут читателям применить свои знания и получить практический опыт. Книга начинается с введения основ программирования на языке R и визуализации данных, подчёркивая важность понимания процесса эволюции технологий и выработки личностной парадигмы восприятия технологического процесса развития современных знаний. Автор утверждает, что эта перспектива необходима для выживания в быстро меняющемся мире и для объединения людей в воюющем государстве.
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