Emergence of Data Science as a Critical Discipline in Biostatistics

Thomas W. MacFarland
Additional contact information
Thomas W. MacFarland: Nova Southeastern University, Office of Institutional Effectiveness and College of Computing and Engineering

Chapter Chapter 1 in Introduction to Data Science in Biostatistics, 2024, pp 1-99 from Springer

Abstract: Abstract The purpose of this lesson is to provide a glimpse of contemporary data science. This lesson will offer a definition of data science, as promulgated by the federal government. There will be extensive discussion on how data science fits into the higher education (e.g., postsecondary, grades 13 and above) curriculum. There is also a discussion on employment opportunities for those who see a future career in which skills in data science are required, with data science either a primary job requirement or at least a secondary job requirement. This lesson also provides a general introduction to R and computing issues inherent to R, where R is used as a platform in data science. The addenda provides more specific information, but still at an introductory level, to the tidyverse ecosystem. Those who wish to use this data science text but are totally new to R should consider reviewing materials from among the many published and free resources on R, either prior to or at least concurrent to the use of this text.

Keywords: Application Programming Interface (API); Assignment Operator; Base R; Beautiful Graphics; Biostatistics; Boolean Selection; Classification of Instructional Programs (CIP); Cloud Computing; Data; Data Harvesting; Data Science; Data Scientist; Dataframe; Datum; Delimited File; Deprecated; Electronic Numerical Integrator and Computer (ENIAC); Graphical User Interface (GUI); Infrastructure as a Service (IaaS); Integrated Postsecondary Education Data System (IPEDS); Moore’s Law; National Institute of Standards and Technology; Occupational Employment and Wage Statistics (OEWS); Occupational Information Network (O*NET); Platform as a Service (PaaS); R; R Function; R Package; Software as a Service (SaaS); Standard Occupational Classification (SOC); Transfer Control Protocol/Internetwork Protocol (TCP/IP); tibble; tidyverse Ecosystem; United States Bureau of Labor Statistics; United States Census Bureau; United States Department of Education (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-46383-9_1

Ordering information: This item can be ordered from
http://www.springer.com/9783031463839

DOI: 10.1007/978-3-031-46383-9_1

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().