Manual of Best Practices in Transparent Social Science Research, written by Garret Christensen (BITSS) with assistance from Courtney Soderberg (Center for Open Science), is a working guide to the latest “best practices” for transparent quantitative social science research. The manual is regularly updated on GitHub. For suggestions or feedback, contact firstname.lastname@example.org.
Implementing Reproducible Research, by Victoria Stodden, Friedrich Leisch, and Roger D. Peng, covers many of the elements necessary for conducting and distributing reproducible research. The book focuses on the tools, practices, and dissemination platforms that aim to ensure reproducibility in computational science.
OpenIntro Statistics is a free comprehensive 400 page online textbook and suite of educational materials on statistics and data analysis.
Reproducible Research is taught by Roger D. Peng, Jeff Leek, and Brian Caffoof at Johns Hopkins University is a course on Coursera that teaches methods on organizing data analysis so that it is reproducible and accessible to others. In this course, students will learn to write a document using R markdown, integrate live R code into a literate statistical program, and compile R markdown documents using knitr and related tools.
Data Science Certificate, offered on Coursera, is set of nine classes that cover the concepts and tools needed throughout the data science pipeline, from asking the right kinds of questions to making inferences and publishing results.
Other Educational Material
BITSS Transparency Glossary authored by BITSS project scientist Garret Christensen, serves to define important terminology commonly used to discuss issues related to research transparency.
Swirl is a software package for the R programming language that turns the R console into an interactive learning environment. Users receive immediate feedback as they are guided through self-paced lessons in data science and R programming.
Swirlify is an R package that provides a comprehensive toolbox for swirl instructors. The tools included serve to guide instructors through the process of creating interactive educational content for students learning R.
Open Science Training Initiative (OSTI), provides a series of lectures in open science, data management, licensing, and reproducibility for use with graduate students and postdoctoral researchers. The lectures can be used individually as one-off information lectures in aspects of open science, or can be integrated into existing course curriculum. Content, slides, and advice sheets for the lectures and other training materials are being gradually released on the GitHub repository as the official release versions become available.
Software Carpentry offers online tutorials for data analysis including Version Control with Git, Using Databases and SQL, Programming with Python, Programming with R, and Programming with MATLAB.
GitHub training offers free and premium educational material from beginning to advanced levels on GitHub.
Blogs to Follow
Data Colada Thinking about evidence and vice versa.
Retraction Watch Tracking retractions as a window into the scientific process.
Political Science Replication A blog about reproducibility, replication, pre-registration, research transparency and open peer review.