Ten simple rules for teaching yourself R

[...]in a recent survey of science educators, the vast majority of respondents rated data skills (analysis and visualization) as extremely or very important for undergraduate students, but respondents particularly from bachelors-granting institutions also listed “outside of coursework” as the most l...

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Bibliographic Details
Published in:PLoS computational biology 2022-09, Vol.18 (9), p.e1010372-e1010372
Main Authors: Lawlor, Jake, Banville, Francis, Forero-Muñoz, Norma-Rocio, Hébert, Katherine, Martínez-Lanfranco, Juan Andrés, Rogy, Pierre, MacDonald, A. Andrew M
Format: Article
Language:English
Subjects:
APL
Biodiversity
Biology and Life Sciences
Blogs
Colleges & universities
Computer and Information Sciences
Data science
Ecologists
Ecology
Education
Engineering and Technology
Environmental statistics
Machine learning
Methods
Multivariate analysis
Programming languages
Sciences education
Scientific visualization
Skills
Social Sciences
Spatial analysis
Statistical analysis
Students
Study and teaching
Undergraduate study
Visualization
Websites
Workshops
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Summary:[...]in a recent survey of science educators, the vast majority of respondents rated data skills (analysis and visualization) as extremely or very important for undergraduate students, but respondents particularly from bachelors-granting institutions also listed “outside of coursework” as the most likely place for students to learn such skills [3]. Importantly, we write this list of strategies and resources not as the voice of authority of the vast and diverse universe of R users, but simply as a group of quantitative-minded mostly ecologists, generally located in universities across Canada, who have all learned R largely without formal instruction. [...]the Quebec Centre for Biodiversity Science (QCBS) R Workshop Series offers introductory and advanced workshops on data visualization, linear models, multivariate analyses, and more, in both English and French, with freely available slides, code, and companion books on their website. The Coding Club from the University of Edinburgh offers a wide breadth of courses for ecologists and environmental scientists, ranging from data manipulation and statistics to geospatial analysis and machine learning.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1010372