This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data.
oferecido por
Universidade Johns HopkinsInformações sobre o curso
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Resultados de carreira do aprendiz
38%
comecei uma nova carreira após concluir estes cursos
38%
consegui um benefício significativo de carreira com este curso
15%
recebi um aumento ou promoção
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Aprox. 55 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Chinês (simplificado), Italiano, Vietnamita, Coreano, Alemão, Russo, Inglês, Espanhol
O que você vai aprender
Understand analytic graphics and the base plotting system in R
Use advanced graphing systems such as the Lattice system
Make graphical displays of very high dimensional data
Apply cluster analysis techniques to locate patterns in data
Habilidades que você terá
Cluster AnalysisGgplot2R ProgrammingExploratory Data Analysis
Resultados de carreira do aprendiz
38%
comecei uma nova carreira após concluir estes cursos
38%
consegui um benefício significativo de carreira com este curso
15%
recebi um aumento ou promoção
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Aprox. 55 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Chinês (simplificado), Italiano, Vietnamita, Coreano, Alemão, Russo, Inglês, Espanhol
oferecido por
Universidade Johns Hopkins
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.
Programa - O que você aprenderá com este curso
19 horas para concluir
Week 1
This week covers the basics of analytic graphics and the base plotting system in R. We've also included some background material to help you install R if you haven't done so already.
19 horas para concluir
15 vídeos (Total 109 mín.), 6 leituras, 7 testes
17 horas para concluir
Week 2
Welcome to Week 2 of Exploratory Data Analysis. This week covers some of the more advanced graphing systems available in R: the Lattice system and the ggplot2 system. While the base graphics system provides many important tools for visualizing data, it was part of the original R system and lacks many features that may be desirable in a plotting system, particularly when visualizing high dimensional data. The Lattice and ggplot2 systems also simplify the laying out of plots making it a much less tedious process.
17 horas para concluir
7 vídeos (Total 61 mín.), 1 leitura, 6 testes
13 horas para concluir
Week 3
Welcome to Week 3 of Exploratory Data Analysis. This week covers some of the workhorse statistical methods for exploratory analysis. These methods include clustering and dimension reduction techniques that allow you to make graphical displays of very high dimensional data (many many variables). We also cover novel ways to specify colors in R so that you can use color as an important and useful dimension when making data graphics. All of this material is covered in chapters 9-12 of my book Exploratory Data Analysis with R.
13 horas para concluir
12 vídeos (Total 77 mín.), 1 leitura, 4 testes
5 horas para concluir
Week 4
This week, we'll look at two case studies in exploratory data analysis. The first involves the use of cluster analysis techniques, and the second is a more involved analysis of some air pollution data. How one goes about doing EDA is often personal, but I'm providing these videos to give you a sense of how you might proceed with a specific type of dataset.
5 horas para concluir
2 vídeos (Total 55 mín.), 2 leituras, 2 testes
Avaliações
Principais avaliações do ANÁLISE EXPLORATÓRIA DE DADOS
por Y23 de Set de 2017
Very good course! It provide me the foundation in learning how to plot and interpret data. This will definitely strengthen my "R programming" to generate publication type figure for my genomics data!
por CC28 de Jul de 2016
This is the second course I have taken from Roger Peng and both were outstanding. I have a strong math background, but not much of a background in stats, but this course was very approachable for me.
por BS20 de Jun de 2017
The course on Exploratory Data Analysis was highly enjoyable. I used to do a lot of this sort of thing in my job, but now spend more of my time managing people. It is fun to get "hands-on" again.
por IA17 de Jan de 2016
Very nice course, plotting data to explore and understand various features and their relationship is the key in any research domain, and this course teaches the skill required to achieve this.
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