Supporting Data Science in the Statistics Curriculum

Autor/inn/en	Loy, Adam; Kuiper, Shonda; Chihara, Laura
Titel	Supporting Data Science in the Statistics Curriculum
Quelle	In: Journal of Statistics Education, 27 (2019) 1, S.2-11 (10 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Loy, Adam)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1069-1898
DOI	10.1080/10691898.2018.1564638
Schlagwörter	Undergraduate Study; Data Collection; Data Analysis; Statistics; Visual Aids; Information Management; Information Storage; Charts; Databases; College Freshmen; Required Courses; Statistical Analysis; Models; Computer Software + Suchen Sie Ihr Suchwort? Grundstudium; Data capture; Datensammlung; Auswertung; Statistik; Anschauungsmaterial; Procurement of information; Informationsbeschaffung; Informationsspeicherung; Diagram; Diagrams; Diagramm; Tabellarische Überischt; Tabelle; Datenbank; Studienanfänger; Pflichtkurs; Statistische Analyse; Analogiemodell
Abstract	This article describes a collaborative project across three institutions to develop, implement, and evaluate a series of tutorials and case studies that highlight fundamental tools of data science--such as visualization, data manipulation, and database usage--that instructors at a wide-range of institutions can incorporate into existing statistics courses. The resulting materials are flexible enough to serve both introductory and advanced students, and aim to provide students with the skills to experiment with data, find their own patterns, and ask their own questions. In this article, we discuss a tutorial on data visualization and a case study synthesizing data wrangling and visualization skills in detail, and provide references to additional class-tested materials. R and R Markdown are used for all of the activities. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01