课程信息
4.5
2,740 ratings
405 reviews
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....
Stacks

Course 5 of 10 in the

Globe

100% 在线课程

立即开始,按照自己的计划学习。
Calendar

可灵活调整截止日期

根据您的日程表重置截止日期。
Clock

建议:4-9 hours/week

完成时间大约为10 小时
Comment Dots

English

字幕:English

您将学到的内容有

  • Check
    Determine the reproducibility of analysis project
  • Check
    Organize data analysis to help make it more reproducible
  • Check
    Publish reproducible web documents using Markdown
  • Check
    Write up a reproducible data analysis using knitr

您将获得的技能

KnitrData AnalysisR ProgrammingMarkup Language
Stacks

Course 5 of 10 in the

Globe

100% 在线课程

立即开始,按照自己的计划学习。
Calendar

可灵活调整截止日期

根据您的日程表重置截止日期。
Clock

建议:4-9 hours/week

完成时间大约为10 小时
Comment Dots

English

字幕:English

教学大纲 - 您将从这门课程中学到什么

1

章节
Clock
完成时间为 2 小时

Week 1: Concepts, Ideas, & Structure

This week will cover the basic ideas of reproducible research since they may be unfamiliar to some of you. We also cover structuring and organizing a data analysis to help make it more reproducible. I recommend that you watch the videos in the order that they are listed on the web page, but watching the videos out of order isn't going to ruin the story. ...
Reading
9 个视频(共 72 分钟), 3 个阅读材料, 1 个测验
Video9 个视频
What is Reproducible Research About?8分钟
Reproducible Research: Concepts and Ideas (part 1)7分钟
Reproducible Research: Concepts and Ideas (part 2) 5分钟
Reproducible Research: Concepts and Ideas (part 3) 3分钟
Scripting Your Analysis 4分钟
Structure of a Data Analysis (part 1)12分钟
Structure of a Data Analysis (part 2)17分钟
Organizing Your Analysis11分钟
Reading3 个阅读材料
Syllabus10分钟
Pre-course survey10分钟
Course Book: Report Writing for Data Science in R10分钟
Quiz1 个练习
Week 1 Quiz20分钟

2

章节
Clock
完成时间为 3 小时

Week 2: Markdown & knitr

This week we cover some of the core tools for developing reproducible documents. We cover the literate programming tool knitr and show how to integrate it with Markdown to publish reproducible web documents. We also introduce the first peer assessment which will require you to write up a reproducible data analysis using knitr. ...
Reading
9 个视频(共 59 分钟), 2 个测验
Video9 个视频
Markdown5分钟
R Markdown6分钟
R Markdown Demonstration7分钟
knitr (part 1)7分钟
knitr (part 2) 4分钟
knitr (part 3) 4分钟
knitr (part 4) 9分钟
Introduction to Course Project 14分钟
Quiz1 个练习
Week 2 Quiz10分钟

3

章节
Clock
完成时间为 1 小时

Week 3: Reproducible Research Checklist & Evidence-based Data Analysis

This week covers what one could call a basic check list for ensuring that a data analysis is reproducible. While it's not absolutely sufficient to follow the check list, it provides a necessary minimum standard that would be applicable to almost any area of analysis....
Reading
10 个视频(共 60 分钟)
Video10 个视频
RPubs 3分钟
Reproducible Research Checklist (part 1)8分钟
Reproducible Research Checklist (part 2) 10分钟
Reproducible Research Checklist (part 3) 6分钟
Evidence-based Data Analysis (part 1)3分钟
Evidence-based Data Analysis (part 2) 3分钟
Evidence-based Data Analysis (part 3) 4分钟
Evidence-based Data Analysis (part 4) 4分钟
Evidence-based Data Analysis (part 5) 7分钟

4

章节
Clock
完成时间为 3 小时

Week 4: Case Studies & Commentaries

This week there are two case studies involving the importance of reproducibility in science for you to watch....
Reading
5 个视频(共 59 分钟), 1 个阅读材料, 1 个测验
Video5 个视频
Case Study: Air Pollution14分钟
Case Study: High Throughput Biology30分钟
Commentaries on Data Analysis2分钟
Introduction to Peer Assessment 2分钟
Reading1 个阅读材料
Post-Course Survey10分钟
4.5
Direction Signs

35%

完成这些课程后已开始新的职业生涯
Briefcase

83%

通过此课程获得实实在在的工作福利

热门审阅

创建者 AAFeb 13th 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.

创建者 ASJun 23rd 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.

讲师

Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

关于 Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world....

关于 Data Science 专项课程

Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material....
Data Science

常见问题

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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