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.
Informações sobre o curso
Habilidades que você terá
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.
- 5 stars74,14%
- 4 stars21,25%
- 3 stars3,41%
- 2 stars0,75%
- 1 star0,43%
Principais avaliações do ANÁLISE EXPLORATÓRIA DE DADOS
Excellent explanation and adding very good skills on the way of data science specialization.For some slides they should be updated to have working URLs , some seems old and absolute now
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!
This is a great course. The basics are explained very clearly and very easy to understand. I highly recommend this course for those who wish to start in Data Analyst / Data Science track.
When it comes to hierarchical and K-means clustering, the theory wasn't explained clearly. When do we use U and V for what purpose? How does D come in? I'm left confused after this.
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