Clinical trial registries can improve the validity of trial results by facilitating comparisons between prospectively planned and reported outcomes. Previous reports on the frequency of planned and reported outcome inconsistencies have reported …
This webinar (recorded Sept. 27, 2017) introduces how to connect other services as add-ons to projects on the Open Science Framework (OSF; https://osf.io). Connecting services to your OSF projects via add-ons enables you to pull together the …
This video will go over three issues that can arise when scientific studies have low statistical power. All materials shown in the video, as well as the content from our other videos, can be found here: https://osf.io/7gqsi/
Python is a general purpose programming language that is useful for writing scripts to work effectively and reproducibly with data. This is an introduction to Python designed for participants with no programming experience. These lessons can be …
Data Carpentry lesson from Ecology curriculum to learn how to analyse and visualise ecological data in R. Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less …
Python is a general purpose programming language that is useful for writing scripts to work effectively and reproducibly with data. This is an introduction to Python designed for participants with no programming experience. These lessons can be …
Access to data is a critical feature of an efficient, progressive and ultimately self-correcting scientific ecosystem. But the extent to which in-principle benefits of data sharing are realized in practice is unclear. Crucially, it is largely unknown …
Data Carpentry trains researchers in the core data skills for efficient, shareable, and reproducible research practices. We run accessible, inclusive training workshops; teach openly available, high-quality, domain-tailored lessons; and foster an …
The Biology Semester-long Course was developed and piloted at the University of Florida in Fall 2015. Course materials include readings, lectures, exercises, and assignments that expand on the material presented at workshops focusing on SQL and R.