
Overview
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 Reproducible Research course offered by Coursera in partnership Johns Hopkins University 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.
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
Get more details
Visit programme websiteProgramme Structure
Courses include:
- Concepts, Ideas, & Structure
- Markdown & knitr
- Reproducible Research Checklist & Evidence-based Data Analysis
- Case Studies & Commentaries
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 1 months
- 2 hrs/week
Start dates & application deadlines
Language
Delivered
- Self-paced
Disciplines
Statistics Data Science & Big Data View 80 other Short Courses in Statistics in United StatesExplore more key information
Visit programme websiteWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
To obtain additional information about the programme, we kindly suggest that you visit the programme website, where you can find further details and relevant resources.
Make sure you meet all requirements
Visit programme websiteTuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months.
Audit: free access to course materials except graded items|Certificate: a trusted way to showcase your skills|A year of unlimited access with Coursera Plus $199
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.