Reproducible Research (Coursera)

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.

Completing this course will count towards your learning in any of the following programs:

- Data Science: Foundations using R Specialization

- Data Science Specialization

What You Will Learn

- Organize data analysis to help make it more reproducible

- Write up a reproducible data analysis using knitr

- Determine the reproducibility of analysis project

- Publish reproducible web documents using Markdown

Syllabus

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

Week 4: Case Studies & Commentaries

This week there are two case studies involving the importance of reproducibility in science for you to watch.