可重复性研究

Reproducible Research

Learn the concepts and tools behind reporting modern data analyses in a reproducible manner. This is the fifth course in the Johns Hopkins Data Science Specialization.

约翰霍普金斯大学

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可重复性研究
  • 分类: 计算机
  • 平台: Coursera
  • 语言: 英语

课程简介

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.

课程大纲

In this course you will learn to write a document using R markdown, integrate live R code into a literate statistical program, compile R markdown documents using knitr and related tools, and organize a data analysis so that it is reproducible and accessible to others.

背景知识

先学习“数据科学家的常用工具”和“R语言编程”这两套课程。

授课形式

There will be weekly video lectures, quizzes, and peer assessments.

As part of this class you will be required to set up a GitHub account. GitHub is a tool for collaborative code sharing and editing. During this course and other courses in the Specialization you will be submitting links to files you publicly place in your GitHub account as part of peer evaluation. If you are concerned about preserving your anonymity you will need to set up an anonymous GitHub account and be careful not to include any information you do not want made available to peer evaluators.

常见问题

学完这门课,我能得到结课证书吗?
凡顺利完成本课程的学生均可获得由授课老师签发的结课证书。

选修这门课需要准备什么?
学生必须拥有一个激活的Github账户,并安装最新版的R语言和RStudio软件。

这门课与数据科学系列课程之间应该怎样合理安排?
这是该系列课程的第5部,我们强烈建议大家先学习《数据科学家的常用工具》和《R语言编程》这两套课程。

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