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Воспроизводимое исследование, Университет Джонса Хопкинса

4.5
Оценки: 3,159
Рецензии: 453

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: 437

автор: Israel David Diaz Garcia

May 16, 2019

Good material

автор: Rooholamin Rasooli

May 13, 2019

lectures are a little bit theoretical and at some point maybe boring but projects will give you a real experience with data and research reproducibility.

автор: Alán García Bernal

May 02, 2019

A very useful course. It helped me to improve the way I structure the analysis at my current job, especially by keeping track of every transformation I apply to the data I’m working with.

автор: Akram Nakhaei

May 02, 2019

Very fruitful. I enjoyed this lesson very much.

автор: Kehinde Usman

Apr 30, 2019

Nice course

автор: Manuel Esteban-Infantes

Apr 29, 2019

Good - Makes you assimilate the concept and work on it

автор: Charles Makowski

Apr 25, 2019

Great course. This and the previous course in the data scientist specialization are extremely practical and I've found immediate utility in my career.

автор: Chetan Thaker

Apr 22, 2019

This course is very helpful in terms of not only doing the analysis but also getting to know the finer nuances of making a structured markdown document for future reproducible.

автор: Sri Hari

Apr 21, 2019

Good

автор: carlos j martinez

Apr 12, 2019

Great course, good lectures. I learned a lot of usable skills.