Reproducible Research free videos and free material uploaded by Johns Hopkins University Staff .
Week 1: Concepts, Ideas, & Structure
This week will cover the basic ideas of reproducible research since they may be unfamiliar to some of you We also cover structuring and organizing a data analysis to help make it more reproducible I recommend that you watch the videos in the order that they are listed on the web page, but watching the videos out of order isn't going to ruin the story
Week 2: Markdown & knitr
This week we cover some of the core tools for developing reproducible documents We cover the literate programming tool knitr and show how to integrate it with Markdown to publish reproducible web documents We also introduce the first peer assessment which will require you to write up a reproducible data analysis using knitr
Week 3: Reproducible Research Checklist & Evidence-based Data Analysis
This week covers what one could call a basic check list for ensuring that a data analysis is reproducible While it's not absolutely sufficient to follow the check list, it provides a necessary minimum standard that would be applicable to almost any area of analysis
Week 4: Case Studies & Commentaries
This week there are two case studies involving the importance of reproducibility in science for you to watch
This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available This course will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results
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