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Voltar para Pesquisa Reprodutível

Comentários e feedback de alunos de Pesquisa Reprodutível da instituição Universidade Johns Hopkins

4.6
estrelas
4,113 classificações
598 avaliações

Sobre o 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....

Melhores avaliações

AA

12 de fev 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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201 — 225 de 580 Avaliações para o Pesquisa Reprodutível

por Carl W

9 de jul de 2018

Knitr was a nice tool to learn. I can see it being useful.

por V P

3 de jul de 2018

most nicely designed course in the specialization loved it

por Andrew

7 de abr de 2019

One of my favorite courses in the specialization so far.

por Andreas K

12 de dez de 2016

best course so far in the data scienist course package!

por James W

31 de out de 2016

This course helped me very much with my current career.

por Md G M

30 de jul de 2018

Course contents are very good and easy to understands.

por Massimo M

15 de fev de 2018

Very nice course, easy to follow and very well taught.

por Giovanni M C V

16 de fev de 2016

Excellent course with great didactic. Congratulations!

por Chanpreet K

30 de dez de 2018

Good course content. All things explained quite well.

por Dewald O

31 de out de 2018

Such a great course! The instructors are really good.

por César A

16 de jun de 2020

Very nice program and a lot of practical exercices

por Mohammad A

20 de jul de 2018

Great course , very informative and well organized

por Lei S

27 de dez de 2017

Only thing: maybe some lectures should be updated.

por phani v k

7 de jan de 2017

This is a very good course for a begineer like me.

por Laro N P

2 de mai de 2018

Good course. Every new course is a new challenge.

por Shivanand R K

21 de jun de 2016

Great and Excellent thoughts and course material.

por מיקי כ

18 de ago de 2020

Great course. very important for any researcher.

por Trung N T

8 de mai de 2017

The course very good for beginner data scientist

por Damian S

16 de nov de 2021

Interesting course with well prepared exercises

por ILLYA B

12 de out de 2020

The best course of John Hopkins Specialization!

por Akram N

2 de mai de 2019

Very fruitful. I enjoyed this lesson very much.

por Jamie M

26 de out de 2018

Good course. Does exactly what it says it does.

por Utku K

14 de nov de 2016

Good lesson, about an interesting topic for me.

por Predrag M

13 de mar de 2016

One of the best courses in this specialization.

por Bipin K

10 de fev de 2016

great one to know how about researches are done