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Воспроизводимое исследование, Университет Джонса Хопкинса

4.5
Оценки: 3,014
Рецензии: 435

Об этом курсе

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....

Лучшие рецензии

автор: 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.

автор: 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.

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Рецензии: 419

автор: Savitri

Jan 29, 2019

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

автор: Azat Gabdolla

Jan 24, 2019

Amazing course, it introduced the concepts of reproducibility which is used to provide scientific fairness, transparency.

автор: Bruno Rafael de Carvalho Santos

Jan 22, 2019

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

автор: Raul Martinez

Jan 16, 2019

Many times the course goes over the same topic over and over.

автор: Alzum Shahadat Miazee

Jan 08, 2019

A great course that will take you ahead to be a Data Scientist

автор: Anusha Verankki

Jan 03, 2019

Excellent Course - particular useful for anyone doing research and performing any kind of analysis on the observed data.

автор: Chanpreet Kaur

Dec 30, 2018

Good course content. All things explained quite well.

автор: LIWANGZHI

Dec 19, 2018

This course provides me with some new ideas about reproducible research and allows me to learn how to wrie .Rmd files.

автор: Don Moffatt

Dec 10, 2018

Good, but the final project involved too much programming and the size of the data file was unmanageable on my three year old laptop. Could the objectives be met with a smaller data file and less programming?

автор: RAVINENDRA PRATAP

Dec 05, 2018

Learnt a Lot about Documenting Standards and specially Markdown Language and KnitR. Very good tips, Thanks.