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Introduction to data science in biostatistics = using R, the tidyverse ecosystem, and APIs /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Introduction to data science in biostatistics/ by Thomas W. MacFarland.
Reminder of title:	using R, the tidyverse ecosystem, and APIs /
Author:	MacFarland, Thomas W.
Published:	Cham :Springer International Publishing : : 2024.,
Description:	xvii, 528 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Biometry. -
Online resource:	https://doi.org/10.1007/978-3-031-46383-9
ISBN:	9783031463839

Introduction to data science in biostatistics = using R, the tidyverse ecosystem, and APIs /
MacFarland, Thomas W.

Introduction to data science in biostatisticsusing R, the tidyverse ecosystem, and APIs /[electronic resource] :by Thomas W. MacFarland. - Cham :Springer International Publishing :2024. - xvii, 528 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9783031463839

Standard No.: 10.1007/978-3-031-46383-9doiSubjects--Topical Terms:

531975
Biometry.

LC Class. No.: QH323.5

Dewey Class. No.: 570.15195

Introduction to data science in biostatistics = using R, the tidyverse ecosystem, and APIs /
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505 0 $a 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.
520 $a 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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