Informações sobre o curso
4.5
2,733 ratings
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404 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

Curso 5 de 10 no

Data Science Programa de cursos integrados
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Clock

Sugerido: 4-9 hours/week

Aprox. 10 horas restantes
Comment Dots

English

Legendas: English

O que você vai aprender

  • 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

Habilidades que você terá

KnitrData AnalysisR ProgrammingMarkup Language
Stacks

Curso 5 de 10 no

Data Science Programa de cursos integrados
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Clock

Sugerido: 4-9 hours/week

Aprox. 10 horas restantes
Comment Dots

English

Legendas: English

Programa - O que você aprenderá com este curso

1

Seção
Clock
2 horas para concluir

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 vídeos (Total de 72 min), 3 leituras, 1 teste
Video9 videos
Introduction1min
What is Reproducible Research About?8min
Reproducible Research: Concepts and Ideas (part 1)7min
Reproducible Research: Concepts and Ideas (part 2) 5min
Reproducible Research: Concepts and Ideas (part 3) 3min
Scripting Your Analysis 4min
Structure of a Data Analysis (part 1)12min
Structure of a Data Analysis (part 2)17min
Organizing Your Analysis11min
Reading3 leituras
Syllabus10min
Pre-course survey10min
Course Book: Report Writing for Data Science in R10min
Quiz1 exercício prático
Week 1 Quiz20min

2

Seção
Clock
3 horas para concluir

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 vídeos (Total de 59 min), 2 testes
Video9 videos
Coding Standards in R8min
Markdown5min
R Markdown6min
R Markdown Demonstration7min
knitr (part 1)7min
knitr (part 2) 4min
knitr (part 3) 4min
knitr (part 4) 9min
Introduction to Course Project 14min
Quiz1 exercício prático
Week 2 Quiz10min

3

Seção
Clock
1 hora para concluir

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 vídeos (Total de 60 min)
Video10 videos
Communicating Results6min
RPubs 3min
Reproducible Research Checklist (part 1)8min
Reproducible Research Checklist (part 2) 10min
Reproducible Research Checklist (part 3) 6min
Evidence-based Data Analysis (part 1)3min
Evidence-based Data Analysis (part 2) 3min
Evidence-based Data Analysis (part 3) 4min
Evidence-based Data Analysis (part 4) 4min
Evidence-based Data Analysis (part 5) 7min

4

Seção
Clock
3 horas para concluir

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 vídeos (Total de 59 min), 1 leitura, 1 teste
Video5 videos
Caching Computations11min
Case Study: Air Pollution14min
Case Study: High Throughput Biology30min
Commentaries on Data Analysis2min
Introduction to Peer Assessment 2min
Reading1 leituras
Post-Course Survey10min
4.5
Direction Signs

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comecei uma nova carreira após concluir estes cursos
Briefcase

83%

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Melhores avaliações

por AA•Feb 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.

por AS•Jun 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.

Instrutores

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

Sobre 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....

Sobre o Programa de cursos integrados Data Science

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

Perguntas Frequentes – FAQ

  • 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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