Retour à Exploration analytique de données

4.7

stars

5,062 évaluations

•

719 avis

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....

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!

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.

Filtrer par :

par Bartlomiej W

•Feb 06, 2016

Some parts of material is good quality, but some is bad - also some show bad practices in R. Extensively use swirl as assignments over self work. It is better to go through good tutorial over R base plotting system and ggplot2.

par David I

•Mar 26, 2016

The final project did not require use of the material in the course beyond the first week and a half. I did not take any quizzes or otherwise have my knowledge tested on the material in the second half of the course.

par Rohith J

•Dec 14, 2016

Course content and assignments were difficult to follow. Loads of statistical content along with high-level R content means it was probably the toughest of the 4 I have taken so far in the Coursetrack.

par Dmitry R

•Feb 06, 2016

some swirl tests (4,5) don't work because of parameter method in qplot function. This parameter is not realy existed in this function now

par Freddie K

•Apr 05, 2017

Quite repetitious in covering basic graphing, and very shallow in regards of clustering, SVD and PCA.

par Tamaz L

•Apr 05, 2016

Very unprofessional, compared to other courses. It wasn't well organized.

par Desmond W

•Oct 19, 2016

About plotting in R. Not about generating real insights from EDA.

par Esther L

•Aug 22, 2019

Too weak regarding the clustering methods, very disappointed.

par ewa b

•May 31, 2017

didnt get much useful-- a whole "course" on plotting? meh.

par Michal K

•May 10, 2016

too superficial

par Piyush V

•Jun 21, 2016

Veyr boring

par Josh H

•Nov 05, 2017

I can't help but feel lied to. The FAQ for the specialization says the following: "We also suggest a working knowledge of mathematics up to algebra (neither calculus or linear algebra are required). " If no linear algebra background is required, then why do you assume that I know what a singular value decomposition is? Or principal components analysis? Terrible course.

par Christy P

•Aug 25, 2017

How can you have a course on Graphic Devices and not show one screen shot of a graphic or open R to show how to perform the ideas around this topic?

par Nicholas

•Sep 30, 2016

NEEEEEED TO EDIT MY PEER REVIEW FROM OTHERS

par Carsten J

•Mar 01, 2016

Material is to basic for an entire course.

par omar k

•Oct 10, 2017

limited and monotonous explanation

Coursera propose un accès universel à la meilleure formation au monde,
en partenariat avec des universités et des organisations du plus haut niveau, pour proposer des cours en ligne.