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Exploratory Data Analysis, Johns Hopkins University

4.7
4,405 ratings
636 reviews

About this Course

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....

Top reviews

By CC

Jul 29, 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.

By Y

Sep 24, 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!

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608 Reviews

By Faylene Therese Gilles

Mar 24, 2019

Very good content !

By Janet Aguayo Reyes

Mar 14, 2019

thank you

By Paul Ringsted

Mar 12, 2019

This course covers plotting (base, lattice, ggplot) then takes a confusing tour into heavy topics of clustering and dimension reduction, then flips back to coloring in charts. The order of the lectures is confusing and PCA/SVD needs more background, clearer explanation and treatment (gets covered a bit more later under regression). Assignments are good and swirl courses helped solidify the lectures.

By Mohammad Amir Aghaee

Mar 11, 2019

It was a very useful course with some meaningful homework. My only criticism is that sometimes the theory and the practice are not well connected. Particularly the discussion of PCA, hierarchical clustering, k-means clustering and others. It would be benefit by providing more meaningful reading for those interesting in better connecting the two

By Glenn Walters

Mar 02, 2019

I really enjoyed this course. I was a good reminder of what analysts need to do when looking at a new dataset. Dr. Peng does a great job walking through the steps and there is enough information given to enable the student to effectively explore on their own.

By Rizwan Mohamed

Mar 01, 2019

please provide some practical problems with answers to practise before attempting the assignments

By Abhay Srivastava

Feb 24, 2019

awesome....

By RobinGeurts

Feb 21, 2019

End assignement was relatively easy compared to the examples in the lectures

By Cynthia Mcgowan Poole

Feb 21, 2019

I learned so much in this course.

By Rooholamin Rasooli

Feb 16, 2019

I learned a lot from this course. Content which the course covers was a third of what I learnt from this course. the best thing about it is learning the pattern of thinking about exploring a whole new dataset.