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学生对 约翰霍普金斯大学 提供的 可重复性研究 的评价和反馈

4.5
3,663 个评分
521 条评论

课程概述

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....

热门审阅

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.

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.

筛选依据:

101 - 可重复性研究 的 125 个评论(共 504 个)

创建者 Krishna B

May 30, 2017

towards the end of week 1 lectures we can see all the parts of this specialization coming together in a very nice way!

创建者 Prem S

Aug 02, 2017

Nice course,especially it gives you a general idea and foundation on r markdown files if you already know R studio.

创建者 Federico A V R

Jul 27, 2017

This topic is relevant to the field, yet few institutions offer courses on it. Great knowledge, highly recommended.

创建者 Lee Y L R

Feb 02, 2018

Clear sharing of the importance of having proper documentation of data analysis process to enable reproducibility.

创建者 Ann B

Mar 14, 2017

I think this topic is sometimes overlooked, but very necessary. This course did a good job of covering the topic.

创建者 Emily S

May 18, 2016

I think this is an essential course that more people should take. Reproducibility is a huge issue in many fields.

创建者 Courtney R

Oct 07, 2019

I really appreciated the topics covered in this course. Is a wonderful follow-up to the Exploratory Data course.

创建者 Thiago

Aug 12, 2019

course material and projects help a lot in learning and tips on how to better document research and projects

创建者 Gregorio A A P

Aug 26, 2017

Excellent, but I would be grateful if you could translate all your courses of absolute quality into Spanish.

创建者 César A

Jun 05, 2017

I really needed this course to fully understand how to work with R from the raw data to publication. Nice ¡¡

创建者 Jared P

Apr 10, 2016

Loved it. The concepts around reproducible research are important. Should be mandatory teaching in school.

创建者 Suryadipta D

Apr 12, 2018

well organized and easy-to-understand subject material, shapes up really well towards the specialization.

创建者 Marco C

Feb 25, 2018

Very useful course to build a scientific way of thinking, and publishing my work has been very engaging.

创建者 santiago R

Nov 29, 2017

Very nice course. R Markdown make everything looks better and understandable for a reproducible research.

创建者 Yasel G S

Aug 04, 2016

This course was very important for my work. I learned so much and I want to say thanks to the professors.

创建者 Shreyas G M

May 01, 2016

Excellently designed course! I loved how the course content and assignments were designed and delivered.

创建者 sneha

Apr 16, 2018

the best course I have ever come across which gives us an idea about knitter and markdown packages in r

创建者 Mauricio V

Dec 13, 2016

excellent course, specially all the topics related to markdown, rpubs. A must for each data scientist.

创建者 Timothy M S J

Nov 29, 2016

Great class. It helps frame all that you will do as a Data Scientist. Building blocks. Peng nails it.

创建者 Edwin L A

Aug 13, 2017

Excelente, sigo en el proceso muy animado y trabajando duro, ha sido una experiencia muy importante.

创建者 Jacques d P

Apr 11, 2018

How to implement reproducible research is an essential skill for all data scientists. Good course.

创建者 Mihai C

Mar 08, 2016

Very pragmatic course, tremendously useful not just for research but also for commercial projects.

创建者 Mathew K

Jan 13, 2020

A pretty good coverage on the need for reproducibility and the best practices to make it happen.

创建者 Christoph G

Jul 09, 2016

This was really valuable in terms of how to document correctly and produce reproducable reports.

创建者 Bruno R d C S

Jan 22, 2019

A great introduction to basics of scientific method concerning statistics and result reporting.