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.
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The book is well illustrated and includes input (in green) and output (in red) of sessions in the projects. The charts produced by the graphical tools are readable and serve as models for exploratory graphics. The data files are large zip files that can be downloaded from the publisher using the included uniform resource locators (URLs). The wealth of projects and the guidance provided to users would make this book very useful in advanced-level practicum/lab courses. (Anthony J. Duben, Computing Reviews, March 13, 2025)
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.
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.
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