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.
About this Course
What you will learn
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
Skills you will gain
- Cluster Analysis
- R Programming
- Exploratory Data Analysis
Syllabus - What you will learn from this course
- 5 stars74.15%
- 4 stars21.25%
- 3 stars3.40%
- 2 stars0.74%
- 1 star0.43%
TOP REVIEWS FROM EXPLORATORY DATA ANALYSIS
This is a great introductory course on the topic and on R language.
You will get acquainted with basic R functions which are most useful for initial statistical analysis.
For someone new to data analytics, this was another great, rewarding course. But as with the others, it demands exploration beyond the lectures and course materials.
This was incredibly useful because it gives you a feel for the datasets and tools with which to explore them. I really wasn't aware of the base and lattice plotting systems until now.
Week 3 - clustering concepts appear hard to comprehend initially. This week should first start with a practical example/use of clustering and then move on to technical
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