Resources

This class is designed for first-time and longer-term users of Jupyter Notebooks, a workspace for writing code. The class focuses on using Notebooks to facilitate sharing and publishing of script workflows. It aims to provide users with knowledge …

This video is an introduction to power analyses to improve the reproducibility of your research.

This video will introduce how to calculate statistical power in R using the pwr package. All materials shown in the video, as well as content from our other videos, can be found here: https://osf.io/7gqsi/.

This is a recording of a 45 minute introductory webinar on preprints. With our guest speaker Philip Cohen, we’ll cover what preprints/postprints are, the benefits of preprints, and address some common concerns researcher may have. We’ll show how to …

The goal of this lesson is to provide an introduction to R for learners working with geospatial data. It is intended as a pre-requisite for the R for Raster and Vector Data lesson for learners who have no prior experience using R. This lesson can be …

An introduction to the concepts and best practices of research data management.

Command line interface (OS shell) and graphic user interface (GUI) are different ways of interacting with a computer’s operating system. The shell is a program that presents a command line interface which allows you to control your computer using …

Data Carpentry lesson to learn to navigate your file system, create, copy, move, and remove files and directories, and automate repetitive tasks using scripts and wildcards with genomics data. Command line interface (OS shell) and graphic user …

Web scraping is the process of extracting data from websites. Some data that is available on the web is presented in a format that makes it easier to collect and use it, for example in the form of downloadable comma-separated values (CSV) datasets …

Today we are going to learn the basics of literate programming using Jupyter Notebooks, a popular tool in data science, with the R kernel, so we can run R code in our notebooks. We’ll then take a look at how we use Git and GitHub to keep track of all …