Topics covered:
Understanding reproducible research
Setting up a reproducible project
Understanding power
Preregistering your study
Keeping track of things
Containing bias
Sharing your work
Various fields in the natural and social sciences face a ‘crisis of confidence’. Broadly, this crisis amounts to a pervasiveness of non-reproducible results in the published literature. For example, in the field of biomedicine, Amgen published …
Modern scientific research takes advantage of programs such as Python and R that are open source. As such, they can be modified and shared by the wider community. Additionally, there is added functionality through additional programs and packages, …
This is the website for the Autumn 2014 course “Reproducible Research Methods” taught by Eric C. Anderson at NOAA’s Southwest Fisheries Science Center. The course meets on Tuesdays and Thursdays from 3:30 to 4:30 PM in Room 188 of the Fisheries …
Description
This hands-on tutorial will train reproducible research warriors on the practices and tools that make experimental verification possible with an end-to-end data analysis workflow. The tutorial will expose attendees to open science …
Workshop goals
- Why are we teaching this
- Why is this important
- For future and current you
- For research as a whole
- Lack of reproducibility in research is a real problem
Materials and how we'll use them
- Workshop landing page, with
- links …
Since 1998, Software Carpentry has been teaching researchers the computing skills they need to get more done in less time and with less pain. Our volunteer instructors have run hundreds of events for more than 34,000 researchers since 2012. All of …
Course summary
A minimal standard for data analysis and other scientific computations is that they be reproducible: that the code and data are assembled in a way so that another group can re-create all of the results (e.g., the figures in a paper). …