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.
ジョンズ・ホプキンズ大学（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.
- 5 stars74.14%
- 4 stars21.25%
- 3 stars3.41%
- 2 stars0.75%
- 1 star0.43%
Great in-depth content about techniques related to exploratory data analysis and implementation in R language using R Studio. Definitely recommend this course to any aspiring data scientist!
Great intro to plotting and related tools in R. Will say that the coverage of heatmaps and PCA felt a little out of left field, with very little intuition. However, overall quite good.
Amazing! Learing so much how to explore the data for the first time. This is a must do for anyone who wants to be a data scientist. Now I can use ggplot without any trouble. Thanks!
Nice course, but too much focus on "R" as a tool.... Industries don't use R as much... The course must be made more generic and independent of R - understand it is not easy to do but ....