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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

4.6
4,115 个评分

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 12, 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

Aug 19, 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."

筛选依据:

451 - 可重复性研究 的 475 个评论(共 580 个)

创建者 Thej K

Mar 12, 2019

Nothing serious in this course! Rmd is a good tool to work with! and get familiar with!

创建者 Jean-Philippe M

Jun 30, 2019

Lack of practical cases. The two cases are not really interesting and lack of details.

创建者 Ян Ш

Jul 16, 2018

The final task can be interpreted too widely. Do I need to pre-clean fuzzy data?

创建者 Freddie K

Apr 16, 2017

Great course! Starting to put pieces from earlier courses together into a whole.

创建者 Tim j

Apr 5, 2017

decent course, it is as long as you make it but start the final project early

创建者 Eduardo S B

Nov 27, 2019

The course is nice. However, I think the last assignment is simply too much.

创建者 Sanjay J

Mar 6, 2017

I think it is one of the easiest and most important courses in Data science.

创建者 Huw H

Oct 30, 2017

An interesting course on a topic that often doesn't get a lot of attention.

创建者 Thomas G

Nov 30, 2016

quite redondant with what was done before but very usefull and clear course

创建者 Pieter v d V

May 20, 2018

Nice to have seen once. Could have been condensed into two or three weeks.

创建者 Herminio V

Sep 13, 2016

Very useful material, and great use for presenting data analysis results.

创建者 Savitri

Jan 28, 2019

Nice and the content of the course will help you a lot to work on

创建者 Ashish S

May 17, 2016

This would be very effective for my personal skill enhancement.

创建者 Ankush K

Jan 8, 2018

It's a great course on a topic that is not addressed enough.

创建者 Kennan Y

Jun 13, 2017

More details are needed about the R/knitr specific details

创建者 Juan G

May 27, 2020

Nice Course, it teaches R Markdown with RStudio and Knitr

创建者 Angel M

Mar 11, 2021

Nice course about how present data and make reports.

创建者 Peter E

Sep 15, 2018

One of Peng's lectures was a little quick and loose

创建者 xiang

Jul 31, 2016

Good but not that deep. This should be in 2 weeks.

创建者 Christopher G

Aug 31, 2016

Material was very interesting and I learned a lot

创建者 Ray W

Mar 2, 2016

Good to know the principles here. Thanks.

创建者 Ilia E

Apr 26, 2016

Week1 and Week2 should be swapped I guess.

创建者 Fabien N

Nov 13, 2019

I really liked the assignments projects !

创建者 Shishir S P

Nov 23, 2020

Enjoyed this course while studying it.

创建者 Craig S

Jan 8, 2018

Some good insights into best practice!