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Reproducible Research, Johns Hopkins University

4.5
(3,164 ratings)

Über diesen Kurs

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-Bewertungen

von AA

Feb 13, 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.

von AS

Jun 23, 2017

Of course, I liked this course. There was even an extra non-graded assignment. Plus two graded assignments. Quality instruction videos and lots of practice. Everything a learner needs.

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438 Bewertungen

von Moshe Pilsky

May 22, 2019

The course seems to be based on lectures recorded at different times. Some points discussed are repetitive. the quality of content is good though. I believe the whole material may have to be updated and, potentially, re-recorded.

von Israel David Diaz Garcia

May 16, 2019

Good material

von Rooholamin Rasooli

May 13, 2019

lectures are a little bit theoretical and at some point maybe boring but projects will give you a real experience with data and research reproducibility.

von Alán García Bernal

May 02, 2019

A very useful course. It helped me to improve the way I structure the analysis at my current job, especially by keeping track of every transformation I apply to the data I’m working with.

von Akram Nakhaei

May 02, 2019

Very fruitful. I enjoyed this lesson very much.

von Kehinde Usman

Apr 30, 2019

Nice course

von Manuel Esteban-Infantes

Apr 29, 2019

Good - Makes you assimilate the concept and work on it

von Charles Makowski

Apr 25, 2019

Great course. This and the previous course in the data scientist specialization are extremely practical and I've found immediate utility in my career.

von Chetan Thaker

Apr 22, 2019

This course is very helpful in terms of not only doing the analysis but also getting to know the finer nuances of making a structured markdown document for future reproducible.

von Sri Hari

Apr 21, 2019

Good