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| dc.contributor.author | Bonsma-Fisher, Madeleine | |
| dc.contributor.author | Coome, Lindsay | |
| dc.contributor.author | Johnston, Luke | |
| dc.contributor.author | Mahallati, Sara | |
| dc.contributor.author | Östblom, Joel | |
| dc.contributor.author | Sales de Andrade, Elliott | |
| dc.contributor.author | Tran, Lina | |
| dc.contributor.author | Santangelo, James | |
| dc.contributor.author | Hasan, Ahmed | |
| dc.contributor.author | Humphries, Zoe | |
| dc.contributor.author | Hoi, Amber | |
| dc.creator | Bonsma-Fisher, Madeleine | |
| dc.creator | Coome, Lindsay | |
| dc.creator | Johnston, Luke | |
| dc.creator | Mahallati, Sara | |
| dc.creator | Östblom, Joel | |
| dc.creator | Sales de Andrade, Elliott | |
| dc.creator | Tran, Lina | |
| dc.creator | Santangelo, James | |
| dc.creator | Hasan, Ahmed | |
| dc.creator | Humphries, Zoe | |
| dc.creator | Hoi, Amber | |
| dc.date.accessioned | 2020-08-20T22:45:39Z | |
| dc.date.available | 2020-08-20T22:45:39Z | |
| dc.date.issued | 2019-06-06 | |
| dc.identifier | 5b163f43-e67b-433e-a8ca-4dc07570c4fa | |
| dc.identifier.uri | https://openlibrary-repo.ecampusontario.ca/jspui/handle/123456789/765 | |
| dc.language.iso | eng | en_US |
| dc.relation.isformatof | https://uoftcoders.github.io/rcourse/index.html | |
| dc.relation.haspart | Instructor Resources: Journal Article | https://jose.theoj.org/papers/10.21105/jose.00049 | |
| dc.relation.haspart | Instructor Resources: GitHub Repository | https://github.com/uoftcoders/rcourse | |
| dc.rights | CC BY | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.subject | Ecology | |
| dc.subject | Statistical analysis | |
| dc.subject | Data simulation | |
| dc.title | Quantitative Methods in R for Biology Course | en_US |
| dc.type | Learning object | |
| dcterms.accessRights | Open Access | |
| dcterms.educationLevel | University - Undergraduate | |
| dc.identifier.slug | https://openlibrary.ecampusontario.ca/catalogue/item/?id=5b163f43-e67b-433e-a8ca-4dc07570c4fa | |
| ecO-OER.Adopted | Yes | |
| ecO-OER.AncillaryMaterial | Yes | |
| ecO-OER.InstitutionalAffiliation | University of Toronto | en_US |
| ecO-OER.ISNI | 0000 0001 2157 2938 | |
| ecO-OER.Reviewed | No | |
| ecO-OER.POD | No | |
| dc.identifier.doi | https://zenodo.org/badge/latestdoi/97400494 | |
| ecO-OER.AccessibilityStatement | Unknown | |
| lrmi.learningResourceType | Educational Unit - Course | |
| lrmi.learningResourceType | Instructional Object - Lecture Material | |
| lrmi.learningResourceType | Instructional Object - Syllabus/Curriculum | |
| lrmi.learningResourceType | Assessment - Measure/Instrument | |
| lrmi.learningResourceType | Assessment - Formal Assessment | |
| ecO-OER.POD.compatible | No | |
| dc.description.abstract | Quantitative Methods in R for Biology is a course aimed at undergraduates at a third year level or above. The course covers statistics and data analysis for ecology and reproducible quantitative methods in R. Statistical analysis, modelling, and data simulation are essential skills for ecologists and evolutionary biologists. Furthermore, ever larger datasets are quickly becoming the norm in a variety of scientific disciplines. This course is therefore designed to meet a growing demand for reproducible, openly accessible, analytically thorough, and well-documented science. Students will learn to develop ecological population models, analyze large datasets, and document their research using the R programming language. No prior programming experience is required. | en_US |
| dc.subject.other | Sciences - Biology | |
| dc.subject.other | Technology - Programming & Programs | |
| dc.subject.other | Technology - Research & Data | |
| ecO-OER.ItemType | Assessment | |
| ecO-OER.ItemType | Course | |
| ecO-OER.ItemType | Instructional Object | |
| ecO-OER.MediaFormat | Other (zipped archive) |
