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Opiniones y comentarios de aprendices correspondientes a Reproducible Research por parte de Universidad Johns Hopkins

4.6
estrellas
4,045 calificaciones
577 reseña

Acerca del Curso

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....

Principales reseñas

AA
12 de feb. de 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.

RR
19 de ago. de 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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551 - 559 de 559 revisiones para Reproducible Research

por Victor M

8 de dic. de 2017

Last two weeks do not teach anything new

por Cyriana R

1 de jul. de 2017

ok, but the focus is too much on knitr,

por Sindre F

1 de ago. de 2016

Useful for academics.

por Avolyn F

19 de jun. de 2019

I was really passionate about the subject matter, but, although I have experience in R, apparently not enough to complete the assignment. Would have liked a little more warning that this would be needed, I was more interested in the topic of Reproducible Research, which while I agree is easier done via code of some kind, shouldn't be a topic specific to R, should be applicable to Python, SQL, whatever.

Might have time to revisit this, but will probably need to take a few more R classes to even be able to complete, likely won't get around to it, but the first 2 weeks were worth the cost of paying for a certificate, I guess.

por Joel K

1 de feb. de 2016

The other modules that I have done in this specialisation have been great. The lecturers are insightful and the courses have been at the right pace. This particular module was flat, to say the least. I paid €43 to learn a small amount of markdown syntax, and the quizzes and the weeks didn't even match up!

por matthieu c

10 de jun. de 2017

The course presented an important topic, but it was not new to me. Moreover I believe that the quality of some audio track is not good enough to understand everything the lecturer is explaining. I'm referring to Roger Peng lecture with the students.

por Stefan H

1 de jul. de 2019

Very repetitive in context of earlier introduction to the topic and also throughout the weeks. Generally it doesn't feel there is much of a take-away and not sure it deserves its own course.

por YAN N W T

11 de oct. de 2017

Not much to take in this course comparing to the previous courses. Worst of all video lectures are not well organised.

por Anand M

5 de may. de 2017

Too much repetition; one video has been stretched into 10.