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UofTCoders/rcourse: Quantitative Methods in R for Biology

Luke W Johnston; Madeleine Bonsma-Fisher; Joel Ostblom; Ahmed Hasan; James Santangelo; Lindsay Coome; Lina Tran; Elliott Sales de Andrade; Sara Mahallati


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      <creatorName>Luke W Johnston</creatorName>
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      <creatorName>Madeleine Bonsma-Fisher</creatorName>
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      <creatorName>Joel Ostblom</creatorName>
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      <affiliation>University of Toronto</affiliation>
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    <creator>
      <creatorName>Ahmed Hasan</creatorName>
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      <affiliation>University of Toronto</affiliation>
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      <creatorName>James Santangelo</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-5921-2548</nameIdentifier>
      <affiliation>University of Toronto</affiliation>
    </creator>
    <creator>
      <creatorName>Lindsay Coome</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-8126-3571</nameIdentifier>
      <affiliation>University of Toronto</affiliation>
    </creator>
    <creator>
      <creatorName>Lina Tran</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-3504-4524</nameIdentifier>
      <affiliation>University of Toronto</affiliation>
    </creator>
    <creator>
      <creatorName>Elliott Sales de Andrade</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-7310-8942</nameIdentifier>
      <affiliation>University of Toronto</affiliation>
    </creator>
    <creator>
      <creatorName>Sara Mahallati</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-6765-0898</nameIdentifier>
      <affiliation>University of Toronto</affiliation>
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  <titles>
    <title>UofTCoders/rcourse: Quantitative Methods in R for Biology</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>R</subject>
    <subject>programming</subject>
    <subject>open source education</subject>
    <subject>learning module</subject>
    <subject>data analysis training</subject>
    <subject>coding</subject>
    <subject>statistics</subject>
    <subject>ecology</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-06-06</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="InteractiveResource"/>
  <alternateIdentifiers>
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  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsSupplementTo">https://github.com/UofTCoders/rcourse/tree/v2.2.0</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1117432</relatedIdentifier>
  </relatedIdentifiers>
  <version>v2.2.0</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This material contains modular participatory live-coding lectures covering statistics and data analysis for ecology and reproducible quantitative methods in R. Statistical analysis, modelling, simulation, and data analysis are essential skills for applying ecology concepts to data. This material is designed to meet a growing demand for reproducible, openly accessible, analytically thorough, and well documented science.&lt;/p&gt;

&lt;p&gt;Website: https://uoftcoders.github.io/rcourse/&lt;/p&gt;</description>
  </descriptions>
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