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Learner Reviews & Feedback for Reproducible Research by Johns Hopkins University

4,167 ratings

About the Course

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....

Top reviews


Feb 12, 2016

My favorite course, at least it gives me an argument why scripted statistics is awesome and can be applied to a number of data related activities. Recycling chunks of code has proven useful to me.


Aug 19, 2020

A very important course that greatly improved my ability to communicate the findings of any sort of data analysis that I perform. This is a critical skill to acquire to "deliver the means."

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526 - 550 of 586 Reviews for Reproducible Research

By Rashaad J

Oct 3, 2017

This is a good course for people who don't have experience with conducting research. For experienced researchers, the content provided is not too informative. More discussions on R Markdown should have been provided.

By Hua-Poo S

Feb 19, 2017

I had difficultly with the two assignments, not because they were difficult but because the instructions were not clear. From reviewing other's assignments, it did not appear to be just me.

By Tony W

Jul 16, 2016

Has interesting ideas and approach to forming a structure way of analysing a problem. The module does feel a little thin in content, and perhaps should be combined with Exploratory Analysis.


Dec 12, 2017

A bit too much focused on academic research, I find. Quality of the video's isn't always top-notch either.

Good exercises to practice plotting skills with interesting, real-life data sets.

By Brittany S

Nov 1, 2018

I wish they'd stop labeling the course projects as two hours. The week 4 project took a lot longer than that (closer to a week). Also, a lot of the information presented was repetitive.

By Chris N

Jan 10, 2022

Course content was relevant. Quality of interactions / other students work was very poor. I had to report twice as many students for plagerism than had valid scripts to assess???

By Rose G

Mar 31, 2020

Good introduction to Rpubs, and important remainder of the importance of reproducible research for scientists, but it may be a bit too much to focus an entire course only on that.

By Michał M

Jan 28, 2016

Some of the videos has low quality, which make them harder to understand for non native speakers. In my opinion there is also too less tips for second assessment.

By Oña G L E

Aug 23, 2018

The videos doesn't listen well, and some activities are not interesting, you could teach swave and some of latex instead of repeat some parts of other courses.

By Bauyrjan J

Sep 1, 2017

This course has contents that are repeated multiple times throughout the course. I think entire course could have been covered in a week or at most two weeks.

By Joseph C

Feb 8, 2016

The first week assignment should really be the second week assignment since all the lessons about knitr would have made the assignment much easier.

By Andreas S J

Oct 4, 2017

Important and interesting stuff - but lots of it is repeated too much, which make it seem like 4 weeks is too much for the material.

By Fabiano S

Mar 7, 2016

It's, for sure, a necessary content but don't feel like something that deserves to be on this specialization. Content is good.

By James O

Oct 31, 2016

Interesting material, but wasn't necessarily of the same depth of knowledge like previous courses in the series

By Fabiola J C

Jan 9, 2021

I experience that the course does not cover all the necessary tools to tackle the final assignment with ease.

By Diego T B

Nov 17, 2017

This topic is very interesting. But I think that was very large and without as practical things in videos.

By Robert K

Jun 12, 2017

This information is useful, but it felt like this could have been condensed in to a couple of weeks.

By Raushon K

Feb 17, 2016

Week1 can be explained better. First assignment i was clueleass on Kintr and how to generate report.

By Nathan M

Jun 11, 2016

Why is this its own class? Seems like it could have been covered in a week somewhere else.

By Jingqin L

Apr 28, 2021

Cover some essential issue in reproducible research but don't touch much on some details.

By Rohit S A

Oct 20, 2016

Not a well structured course. Also, not very motivating to go through this one.

By Fernando M

Sep 4, 2017

Don´t like this topics but I understand that they are necessary. Course is ok

By Corbin C

Apr 23, 2018

Good material, but some of it is out of date (like deprecated functions).

By Shuwen Y

Jul 9, 2016

content is not enough for one class. should be only one to two videos.

By Martin G

Aug 3, 2019

Interesting content. However, it can get somewhat repetitive.