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Learner Reviews & Feedback for Exploratory Data Analysis by Johns Hopkins University

4.7
stars
6,014 ratings

About the 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

CC

Jul 28, 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.

Y

Sep 23, 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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701 - 725 of 851 Reviews for Exploratory Data Analysis

By Kamal D

Jun 1, 2021

Only the 3rd week was confusing but the confusion was revoked by swirl package

By Philip W

Mar 21, 2017

Would have needed a litle more in depth explanation of the clustering analysis

By Subramanya N

Dec 12, 2017

ggplot should have been given more emphasis. It warrants a course on its own!

By Greg R

May 30, 2016

Pretty good course. Nice content. Middle section on clustering felt random.

By Pavel B

Feb 18, 2016

I like the course and it was helpful in understanding how graphics work in R.

By RobinGeurts

Feb 21, 2019

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

By Mario S P G

Sep 17, 2018

Good beginners course with helpful tools to take a first glance to your data

By Polina

Apr 25, 2018

Nice course, very useful. I wish the links were updated more often, however.

By Jan W v d L

Feb 14, 2021

Learned a lot, the cluster and kmeans could have been more explained though

By Gao Q

Jul 23, 2018

Great content for beginners to get familiar with various graphic tools in R

By Mario P

Jan 20, 2018

I suggest to shift a little more the focus on svd and clustering techniques

By Olga H

Sep 22, 2017

Good course, would have likes more practice & testing on the clustering stu

By Andrew W

Mar 19, 2018

Challenging but great fun and really helped me to get more familiar with R

By Carlos L

Jun 22, 2016

swirl is very used in this course. It is one of the best tools to learn R

By Sarfaraz U A

Aug 20, 2021

Nice course but it would have been better if more theory was covered.

By Caio H F A

Apr 22, 2020

Nice but the projects are way harder than the lessons and quizzes;

By Anirban C

Jul 19, 2017

Nice course! Assignments could have been a little more challenging

By Ankit A

Dec 16, 2016

The exploratory part was very good. But, PCA was a waste of time.

By Jeff B

Mar 4, 2018

The plotting aspects of this course appealed to my visual sense.

By Ashish S

May 17, 2016

This would be very effective for my personal skill enhancement.

By Pierre D

Feb 3, 2016

More challenging Problem sets, as in the R Programming course !

By Frederik C

May 23, 2018

High quality course, but the order of lectures is not perfect

By Richard D

Jun 12, 2017

Great overview, especially the parts on dimension reduction.

By YOGESH R

Sep 30, 2020

sorry, but I didn't understood much from 3rd and 4th week..

By Sakshat R

Jul 3, 2020

Really nice course! Great instructor and good case studies!