Tools

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007 cr |||||||||||;

008 250618s2025 flub ob 001 0 eng d;

015 a| GBC5648762| bnb;

016 7 a| 3005695942| Uk;

020 a| 104037011Xq| (electronic bk.);

020 a| 9781040370117q| (electronic bk.);

020 a| 9781003423386q| (electronic bk.);

020 a| 1003423388q| (electronic bk.);

020 a| 1040370136q| (electronic bk. : EPUB);

020 a| 9781040370131q| (electronic bk.);

024 7 a| 10.1201/97810034233862| doi;

024 8 a| CIPO000238624;

035 a| (Sirsi) o1523841825;

035 a| (OCoLC)1523841825;

037 a| 9781003423386b| Taylor & Francis;

049 a| NEHH;

050 4 a| QA276.45.R3b| .P38 2025e;

082 04 a| 519.5028551332| 23/eng/20250626;

100 1 a| Paul, Alice,e| author.=| ^A1490275;

245 10 a| Mastering health data science using R /c| Alice Paul.;

250 a| First edition.;

264 1 a| Boca Raton, FL :b| CRC Press,c| 2025.;

300 a| 1 online resource (xiii, 358 pages) :b| illustrations;

336 a| textb| txt2| rdacontent;

337 a| computerb| c2| rdamedia;

338 a| online resourceb| cr2| rdacarrier;

504 a| Includes bibliographical references and index.;

520 a| This book provides a practical, application-driven guide to using R for public health and health data science, accessible to both beginners and those with some coding experience. Each module starts with data as the driver of analysis before introducing and breaking down the programming concepts needed to tackle the analysis in a step-by-step manner. This book aims to equip readers by offering a practical and approachable programming guide tailored to those in health-related fields. Going beyond simple R examples, the programming principles and skills developed will give readers the ability to apply R skills to their own research needs. Practical case studies in public health are provided throughout to reinforce learning.Topics include data structures in R, exploratory analysis, distributions, hypothesis testing, regression analysis, and larger scale programming with functions and control flows. The presentation focuses on implementation with R and assumes readers have had an introduction to probability, statistical inference and regression analysis.Key features: Includes practical case studies. Explains how to write larger programmes. Contains additional information on Quarto.;

588 a| Description based on print version record.;

650 0 a| R (Computer program language)=| ^A523882;

650 0 a| Medical informatics.=| ^A149372;

650 0 a| Biomathematics.=| ^A20648;

776 08 i| Print version:z| 9781032729367z| 9781032729930;

856 40 z| Direct link to eBooku| https://ebookcentral.proquest.com/lib/eastcarolina/detail.action?docID=32154972;

949 a| CLICK ON WEB ADDRESSw| ASISh| HSL102p| $303.800| HSLo| HMT;

949 a| CLICK ON WEB ADDRESSw| ASISh| JOYNER96o| HMT;

994 a| C0b| NEH;

596 a| 1 4;

998 a| 6735575;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6735575-1001l| HSLELECm| HSLp| $303.80r| Ys| Yt| HGENEBKu| 6/22/2026x| EBOOKz| HERESOURCE0| HSLo| .STAFF. HMT;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6735575-2001l| JNETm| JOYNERr| Ys| Yt| JNE3BKu| 6/22/2026x| EBOOKz| JERESOURCEo| .STAFF. HMT;

Mastering health data science using R / Alice Paul.

Author/creator	Paul, Alice author.
Format	Electronic
Edition	First edition.
Publication	Boca Raton, FL : CRC Press, 2025.
Description	1 online resource (xiii, 358 pages) : illustrations
Supplemental Content	Direct link to eBook
Subjects	R (Computer program language) Medical informatics. Biomathematics.

Abstract	This book provides a practical, application-driven guide to using R for public health and health data science, accessible to both beginners and those with some coding experience. Each module starts with data as the driver of analysis before introducing and breaking down the programming concepts needed to tackle the analysis in a step-by-step manner. This book aims to equip readers by offering a practical and approachable programming guide tailored to those in health-related fields. Going beyond simple R examples, the programming principles and skills developed will give readers the ability to apply R skills to their own research needs. Practical case studies in public health are provided throughout to reinforce learning.Topics include data structures in R, exploratory analysis, distributions, hypothesis testing, regression analysis, and larger scale programming with functions and control flows. The presentation focuses on implementation with R and assumes readers have had an introduction to probability, statistical inference and regression analysis.Key features: Includes practical case studies. Explains how to write larger programmes. Contains additional information on Quarto.
Bibliography note	Includes bibliographical references and index.
Source of description	Description based on print version record.
Issued in other form	Print version: 9781032729367 9781032729930
ISBN	104037011X (electronic bk.)
ISBN	9781040370117 (electronic bk.)
ISBN	9781003423386 (electronic bk.)
ISBN	1003423388 (electronic bk.)
ISBN	1040370136 (electronic bk. : EPUB)
ISBN	9781040370131 (electronic bk.)
Standard identifier#	10.1201/9781003423386
Standard identifier#	CIPO000238624
Stock number	9781003423386 Taylor & Francis

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