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Johns Hopkins University vía Coursera
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Reproducible Research

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  • 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.