Open Science Platforms, Statistics, Coding & Github
Photo credit: Walter Dellisanti
How to get started in and advocate for open science and reproducibility: Github and R
"When all researchers are aware of Open Science, and are trained, supported and guided at all career stages to practice Open Science, the potential is there to fundamentally change the way research is performed and disseminated, fostering a scientific ecosystem in which research gains increased visibility, is shared more efficiently, and is performed with enhanced research integrity." Open Science Skills Working Group Report (2017)
All below resources are free and completely open source.
Open Science General Resources: Getting Started
Open Science Training Handbook
Center for Open Science Resources
Statistics
Bayesian statistics is an approach to data analysis based on Bayes’ theorem. The Statistical Rethinking (2024) course by Richard Mcelreath introduces statistical modelling using Bayesian techniques.
Coding in R
Getting started with R and R Studio and software Carpentry lessons.
Besides data and statistical analyses, see what else you can do:
Bookdown and R books: Example, getting started
Powerful data visualization: R Graph Gallery
Learn code from others: Like Tidy Tuesdays
Markdown
Markdown is a plain text formatting syntax that allows readers to view document and code without downloading something like Microsoft Word.
Introduction to Markdown using an application like Atom. Every “post” in the open lab notebook example on Github is written using Markdown syntax.
Github
“GitHub is a code hosting platform for version control and collaboration. It lets you and others work together on projects from anywhere.”
The Basics: Github guides, Intro for Beginners, Use Git with R
Create your own webpage: Github Pages
Open Lab Notebooks and Protocol Sharing: Example
Publish Markdown Resources: Example
Love coding and data visualization? Host a webinar with us!
Photo credit: D. Juszkiewicz