Introduction to Data Science in Biostatistics

Using R, the Tidyverse Ecosystem, and APIs
Erscheinungsjahr 2025
ISBN: 978-3-031-46385-3
Verlag: Springer International Publishing

Buch, Englisch, 528 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 820 g

Introduction to Data Science in Biostatistics: Using R, the Tidyverse Ecosystem, and APIs defines and explores the term "data science" and discusses the many professional skills and competencies affiliated with the industry. With data science being a leading indicator of interest in STEM fields, the text also investigates this ongoing growth of demand in these spaces, with the goal of providing readers who are entering the professional world with foundational knowledge of required skills, job trends, and salary expectations.

The text provides a historical overview of computing and the field's progression to R as it exists today, including the multitude of packages and functions associated with both Base R and the tidyverse ecosystem. Readers will learn how to use R to work with real data, as well as how to communicate results to external stakeholders. A distinguishing feature of this text is its emphasis on the emerging use of APIs to obtain data.

Zielgruppe

Graduate

Autoren/Hrsg.

Macfarland, Thomas W.

Fachgebiete

• Naturwissenschaften Biowissenschaften Angewandte Biologie Biomathematik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

1. Emergence of Data Science as a Critical Discipline in Biostatistics.- 2. Data Sources in Biostatistics.- 3. Role of Statistics for Decision Making in Biostatistics.- 4. Data Science and R, Base R, and the tidyverse Ecosystem.- 5. Statistical Analyses and Graphical Presentations in Biostatistics Using Base R and the tidyverse Ecosystem.- 6. Use of R-Based APIs to Obtain Data.- 7. Putting It All Together: R, the tidyverse Ecosystem, and APIs.

Über Autor(innen)

Thomas W. MacFarland, Ed.D., is senior research associate (Office of Institutional Effectiveness) and associate professor (College of Computing and Engineering) at Nova Southeastern University, Fort Lauderdale, Florida. Dr. MacFarland maintains an active research agenda, using R for data organization, statistical analyses, and graphical presentations.