LEADER 03339nam  22006015  450 
001 9910857793403321
005 20251201091908.0
010   $a3-031-46383-8
024 7 $a10.1007/978-3-031-46383-9
035   $a(CKB)31999355900041
035   $a(MiAaPQ)EBC31338227
035   $a(Au-PeEL)EBL31338227
035   $a(DE-He213)978-3-031-46383-9
035   $a(EXLCZ)9931999355900041
100   $a20240510d2024      u|         0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aIntroduction to Data Science in Biostatistics $eUsing R, the Tidyverse Ecosystem, and APIs /$fby Thomas W. MacFarland
205   $a1st ed. 2024.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2024.
215   $a1 online resource (536 pages)
300   $aIncludes index.
311 08$a3-031-46382-X 
327   $a1. 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.
330   $aIntroduction 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.
606   $aBiometry
606   $aArtificial intelligence$xData processing
606   $aStatistics
606   $aQuantitative research
606   $aBiostatistics
606   $aData Science
606   $aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
606   $aData Analysis and Big Data
615  0$aBiometry.
615  0$aArtificial intelligence$xData processing.
615  0$aStatistics.
615  0$aQuantitative research.
615 14$aBiostatistics.
615 24$aData Science.
615 24$aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
615 24$aData Analysis and Big Data.
676   $a570.15195
700   $aMacFarland$b Thomas W.$0721661
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910857793403321
996   $aIntroduction to Data Science in Biostatistics$94161945
997   $aUNINA