Reproducible Research

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4.5

(4)

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Course Features

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Duration

8 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Beginner

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Teaching Type

Self Paced

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Video Content

8 hours

Course Description

This course will focus on the concepts and tools that are used to report modern data analyses in a reproducible way. The idea of reproducible research means that data analyses and, more generally, scientific claims are published together with the data and code to allow others to verify and expand upon the results. As data analyses become more complex and involve larger data sets and more complicated computations, the need for reproducibility has increased dramatically. Because of reproducibility, people can focus on the content of a data analyse rather than on details in a written summary. Reproducibility also makes it easier to share an analysis with others, as the code and data that actually performed the analysis are readily available. This course will teach you how to use literate statistical analysis software to publish data analyses in one document. This allows others to perform the same analysis and get the same results.

Course Overview

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Hands-On Training,Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

What You Will Learn

Organize data analysis to help make it more reproducible

Write up a reproducible data analysis using knitr

Determine the reproducibility of analysis project

Publish reproducible web documents using Markdown

Course Instructors

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Roger D. Peng, PhD

Bloomberg School of Public Health

Roger D. Peng is a Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and a Co-Editor of the Simply Statistics blog. He received his Ph.D. in Statistics from the Univ...
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Jeff Leek, PhD

Bloomberg School of Public Health

Jeff Leek is an Assistant Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and co-editor of the Simply Statistics Blog. He received his Ph.D. in Biostat...

Brian Caffo, PhD

Bloomberg School of Public Health

Brian Caffo, PhD is a professor in the Department of Biostatistics at the Johns Hopkins University Bloomberg School of Public Health. He graduated from the Department of Statistics at the Unive...

Course Reviews

Average Rating Based on 4 reviews

4.6

100%

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