Chevron Left
Back to Exploratory Data Analysis

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

4.7
stars
6,051 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.

YF

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:

201 - 225 of 856 Reviews for Exploratory Data Analysis

By Avizit C A

•

Jan 30, 2019

A very good course describing commonly used graphical techniques with good examples.

By Jacques d P

•

Feb 4, 2018

Enjoyed this course. The course content and projects are very relevant to the field.

By Sean N

•

Feb 14, 2017

A nice introduction to operating on Data sets. Clear examples, interesting projects.

By Lluís G

•

Nov 28, 2016

Very good course that provides handy tools for data manipulation and representation

By Pratyush D

•

Feb 16, 2016

Very good course. Explains some very peculiar concepts of PCA and SVD very clearly.

By Susan M

•

Oct 12, 2020

Sound practicum with challenging and comprehensive projects to solidify skill set.

By Shubham S

•

Oct 7, 2019

Thank you so much instructors, the learning curve till now has been great for me.

By Pooia L

•

Aug 30, 2018

I loved it, it improved my R skills in plotting and also gave me nice insights!!!

By Pradeep S

•

Jan 21, 2018

Very useful subject on churning data to derive meaningful and actionable insights

By Juliana C

•

Sep 25, 2017

Great course to learn how to build nice graphics and do exploratory data analysis

By Zhiming

•

Sep 23, 2017

This course is quite helpful. Especially the part which we learned to use ggplot.

By Jairo A V G

•

Jun 25, 2020

an excellent course that allowed me to expand my knowledge and learn new things.

By Admet Z

•

May 28, 2018

Found this course very impressive and challenging. Looking forward for the next.

By santiago R

•

Nov 14, 2017

Very nice course. good material. Not easy nor boring at all. Really learned here

By Ravi S R

•

Sep 10, 2017

This course is very important for beginners and it is also simple to understand.

By Saikiran K

•

Jun 30, 2016

This course served as a great introduction to R and helped me to get ease with R

By danxu

•

May 22, 2016

Very useful !

Teacher is awesome, statement is clear and simple.

love this course!

By Gayathri N

•

Jun 6, 2020

Explained in a simple and clear way for folks like me who are new to the course

By Raunak S

•

Oct 11, 2018

awesome course to learn exploratory data analysis using R programming language.

By Luiz A M F

•

Dec 26, 2016

Excellent course to develop and understand the technique of data visualization.

By Nipuni D

•

Sep 26, 2021

I have leraned a a lot on basic plotting systems. very helpful for a beiginer

By Angela C

•

Sep 9, 2019

The BEST course in the series by far. You finally get your hands on some data.

By Bruno R S

•

Jan 14, 2019

An excellent introduction to R' basic processing and graphing functionalities.

By Antonio M L

•

Feb 17, 2018

Useful. very clear and easy to review and learn ggplot and other useful things

By antonio q

•

Dec 30, 2017

very good course, a fast and robust was to learn data analysis using R, thanks