1.

Record Nr.

UNINA9910857793403321

Autore

MacFarland Thomas W.

Titolo

Introduction to Data Science in Biostatistics : Using R, the Tidyverse Ecosystem, and APIs / / by Thomas W. MacFarland

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024

ISBN

3-031-46383-8

Edizione

[1st ed. 2024.]

Descrizione fisica

1 online resource (536 pages)

Disciplina

570.15195

Soggetti

Biometry

Artificial intelligence - Data processing

Statistics

Quantitative research

Biostatistics

Data Science

Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences

Data Analysis and Big Data

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Includes index.

Nota di contenuto

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.

Sommario/riassunto

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.