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InteractiveResource . 2019
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UofTCoders/rcourse: Quantitative Methods in R for Biology

appsOther research productkeyboard_double_arrow_right InteractiveResource 15 Jan 2019 English Publisher:Zenodo
Authors: Luke W Johnston; Madeleine Bonsma-Fisher; Joel Ostblom; Ahmed Hasan; James Santangelo; Lindsay Coome; Lina Tran; +2 Authors

doi: 10.5281/zenodo.2540708 , 10.5281/zenodo.1117432 , 10.5281/zenodo.3240508

UofTCoders/rcourse: Quantitative Methods in R for Biology

Abstract

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. Website: https://uoftcoders.github.io/rcourse/

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Keywords

open source education, coding, statistics, R, data analysis training, ecology, programming, learning module

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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