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

4,045 calificaciones
577 reseña

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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

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.

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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151 - 175 de 559 revisiones para Reproducible Research

por Sanat N D

8 de abr. de 2017

I found this course very informative and helpful. The course content is very well organized.

por Manuel M M

21 de nov. de 2019

Nice course. you learn quite a lot of things although it could be a little bit more complex

por 李俊宏

11 de mar. de 2018

I think this one is very important because scientific research always need to be repeated!

por Talant R

24 de oct. de 2016

Great course to learn "knitr" and how to code in reproducible manner!

Totally recommend it!

por Eric K

21 de jun. de 2020

Excellent course. Roger Peng is a fantastic instructor and knows R and data science well.

por Giovanni V

10 de abr. de 2016

This course helped me to apply skills learned in the other courses of the specialization.

por Georgios P

31 de oct. de 2018

I learned how to write and publish reproducible articles in a very short period of time!

por Juliana C

25 de sep. de 2017

Great great course to learn basics on reproducibility, and nice R tools like R Markdown

por Wassim K

26 de may. de 2017

I enjoyed it a lot. the learned material is applicable to any scientific work to be done

por Atair A C j

6 de oct. de 2017

I was able to learn very good base to assure my work can be reproduced within my peers.

por 陈颐欢

10 de jun. de 2018

The concept introduced here is very essential and basic for high quality data analysis

por Rob S

6 de feb. de 2020

very interesting, but a pity about the errors that occur due to incompatible software

por Shubham S

24 de nov. de 2019

Thank you instructors, for making me realize the importance of reproducible research.

por Rodney J

6 de jul. de 2017

This is a great course on a very important topic that every researcher should master.

por Lindy W

18 de dic. de 2016

Learnt some really neat new tools. Favourite course from this specialisation so far.

por Stephan H

9 de oct. de 2017

Nice course. But I'm always worried about the estimated lengths of the assignments.

por Brendan M

28 de feb. de 2017

This was possibly the most important class I took, which was completely unexpected.

por Sai S S

27 de jun. de 2017

Think an assignment after week-3 even if its a fishing expedition would add value.

por Raunak S

11 de oct. de 2018

great course for those wanting to learn basic concepts of Reproducible Research.

por Frederik C

29 de may. de 2018

Key aspect for a good data scientist. It was a nice introduction to knitr etc...

por Jose P

11 de feb. de 2018

Perfect to aid past and present curation and validation of research. Thank you!

por Emil L

3 de nov. de 2016

Great Course, should be free to all freshman graduate students across the world.

por Jim M

22 de may. de 2020

Very nice final course pulling everything together from the previous 4 courses.

por Nilrey J D C

7 de oct. de 2019

A very good course to know why it is important to have a reproducible research.

por Xuwei L

15 de may. de 2016

excellent course to introduce practical approach for reporting data analysis !