Chevron Left
Back to Exploratory Data Analysis

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

4.7
stars
5,921 ratings
864 reviews

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!

Filter by:

701 - 725 of 834 Reviews for Exploratory Data Analysis

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!

By Vebashini N

Nov 14, 2017

Thank you, i learnt a lot and will continue on my journey.

By Rajeev D

Feb 17, 2021

It was a great experience to complete such a good course.

By Sahil S

Jan 24, 2021

Best course of the 4 taken so far in this specialization

By Paul M

Jun 2, 2016

Very good introduction to the various graphing systems.

By Dai Y

Aug 9, 2018

Improvement should be done to the materials of Week 3.

By Giovanni M C V

Feb 16, 2016

Excellent course with great didactic. Congratulations!

By jishuenkam

Aug 27, 2016

Hopefully it could be clearer on dimension reduction.

By Murugesan A

Mar 22, 2017

Well crafted, carefully designed learning materials!

By Dan B

Sep 10, 2018

NIce course, but the lectures are a little tedious

By Alan C

Dec 15, 2019

Decent overview of the graphing fundamentals in R

By Shivanand R K

Jun 21, 2016

Great and Excellent thoughts and course material.

By Mohammad F H

Sep 15, 2016

Very detailed. Like the case study by Dr. Peng.

By Nilrey J D C

Oct 7, 2019

This is a good introduction to do EDA using R.

By Ratnikov Y

May 27, 2017

Clustering is overwhelming field of knowledge.