Reproducible research

dc.contributor.author	Magle, C. Tobin, speaker
dc.date.accessioned	2019-05-07T13:46:21Z
dc.date.available	2019-05-07T13:46:21Z
dc.date.issued	2017-06-26
dc.description	Accessibility features: Transcript.
dc.description.abstract	What is reproducible research? Why should you adopt it? How to use R, git and markdown to make your analysis more efficient and reproducible.
dc.format.extent	30 minutes 10 seconds
dc.format.medium	born digital
dc.format.medium	motion pictures (visual works)
dc.format.medium	digital moving image formats
dc.format.medium	instructional materials
dc.format.medium	transcripts
dc.identifier.uri	https://hdl.handle.net/10217/194886
dc.language	English
dc.language.iso	eng
dc.publisher	Colorado State University. Libraries
dc.relation.ispartof	Training and Instruction
dc.rights	Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.rights.license	This article is open access and distributed under the terms and conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0).
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject	data management
dc.subject	data storage
dc.subject	data education
dc.subject.lcsh	Data editing
dc.subject.lcsh	Data curation
dc.subject.lcsh	Programming languages (Electronic computers)
dc.title	Reproducible research
dc.title.alternative	Data and donuts
dc.type	MovingImage
dc.type	Text

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