<p><div><div><div><div data-show-faces="false" data-height="21" data-width="100" data-layout="button_count" data-send="true" data-href="https://www.r-bloggers.com/enroll-now-in-the-mooc-on-exploratory-multivariate-data-analysis-with-r/"></div></div><div></div></div><div></div></div>
<div>
(This article was first published on <strong><a href="https://francoishusson.wordpress.com/2018/03/04/enroll-now-in-the-mooc-on-exploratory-multivariate-data-analysis-with-r/"> François Husson</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Exploratory multivariate data analysis is studied and has been taught in a “French-way” for a long time in France. You can enroll in a MOOC (completely free) on <strong><a rel="nofollow" href="https://www.fun-mooc.fr/courses/course-v1:agrocampusouest+40001S04EN+session04/about" target="_blank">Exploratory Multivariate Data Analysis</a></strong>. The MOOC will start the 5th of March 2018.</p>
<p><a rel="nofollow" href="https://www.fun-mooc.fr/courses/course-v1:agrocampusouest+40001S04EN+session04/about" target="_blank"><img data-orig-file="https://francoishusson.files.wordpress.com/2017/02/image_cours.png?w=260&amp;h=173&amp;fit=260%2C173&amp;resize=260%2C173" data-orig-size="580,386" data-medium-file="https://francoishusson.files.wordpress.com/2017/02/image_cours.png?w=260&amp;h=173&amp;fit=260%2C173&amp;resize=260%2C173?w=300" data-attachment-id="85" data-image-meta="{" data-image-description="" src="https://francoishusson.files.wordpress.com/2017/02/image_cours.png?w=260&h=173&fit=260%2C173&resize=260%2C173" data-permalink="https://francoishusson.wordpress.com/image_cours/" data-large-file="https://francoishusson.files.wordpress.com/2017/02/image_cours.png?w=260&amp;h=173&amp;fit=260%2C173&amp;resize=260%2C173?w=580" alt="image_cours" data-image-title="image_cours" sizes="(max-width: 260px) 100vw, 260px" width="260" data-comments-opened="1" class="wp-image-85" data-recalc-dims="1" height="173"></a></p>
<p>This MOOC focuses on 5 essential and basic methods, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical and clustering. An extension to Multiple Factor Analysis (MFA) will give you the opportunity to analyse more complex dataset that are structured by groups.</p>
<p>This course is application-oriented and many examples and numerous exercises are done with FactoMineR (a package of the free R software) will make the participant efficient and reliable face to data analysis.</p>
<p>See you soon.</p>
<p> </p>
	<p>
<div>
<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="https://francoishusson.wordpress.com/2018/03/04/enroll-now-in-the-mooc-on-exploratory-multivariate-data-analysis-with-r/"> François Husson</a></strong>.</div>
<hr>
<a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers.com</a> offers <strong><a rel="nofollow" href="https://feedburner.google.com/fb/a/mailverify?uri=RBloggers">daily e-mail updates</a></strong> about <a rel="nofollow" href="https://www.r-project.org/" title="The R Project for Statistical Computing">R</a> news and <a rel="nofollow" href="https://www.r-bloggers.com/search/tutorial" title="R tutorials">tutorials</a> on topics such as: <a rel="nofollow" href="https://www.r-bloggers.com/search/data%20science" title="Data science">Data science</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/Big%20Data" title="Big Data">Big Data, <a rel="nofollow" href="https://www.r-users.com/" title="R jobs">R jobs</a>, visualization (<a rel="nofollow" href="https://www.r-bloggers.com/search/ggplot2" title="ggplot and ggplot2 tutorials">ggplot2</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/boxplot" title="Boxplots using lattice and ggplot2 tutorials">Boxplots</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/map" title="Maps and gis">maps</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/animation" title="Animation in R">animation</a>), programming (<a rel="nofollow" href="https://www.r-bloggers.com/search/RStudio" title="RStudio IDE for R">RStudio</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/sweave" title="Sweave and literate programming">Sweave</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/LaTeX" title="LaTeX in R">LaTeX</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/SQL" title="SQL and databases">SQL</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/eclipse" title="Eclipse IDE for R">Eclipse</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/git" title="git and github, Version Control System">git</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/hadoop" title="Large data in R using Hadoop">hadoop</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/Web+Scraping" title="Web Scraping of google, facebook, yahoo, twitter and more using R">Web Scraping</a>) statistics (<a rel="nofollow" href="https://www.r-bloggers.com/search/regression" title="Regressions and ANOVA analysis tutorials">regression</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/PCA" title="principal component analysis tutorial">PCA</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/time+series" title="Time series">time series</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/trading" title="finance trading">trading</a>) and more...
<img alt="" width="1" src="http://feeds.feedburner.com/~r/RBloggers/~4/0K3ISSEHW_8" height="1"></a></div>