Teaser MOOC Exploratory Multivariate Data Analysis

18 Nov 2016 · 2 min

Watch on YouTube

2:06

This introductory teaser presents a MOOC on exploratory multivariate data analysis aimed at students, researchers, industry professionals, and anyone curious about extracting insights from complex, high‑dimensional datasets. The course promises to teach several multidimensional analysis techniques that examine all variables simultaneously, offering deeper understanding than univariate approaches. A central emphasis is placed on visualizing results—both individuals (as point clouds) and variables (as hierarchical trees)—so that the complementary visual outputs aid interpretation. Each method is illustrated with real‑world data, accompanied by intuitive, step‑by‑step explanations. Learners will engage with quizzes and practical R exercises to apply the methods and learn to interpret the outputs, culminating in the ability to run and understand these analyses independently. The speakers invite viewers to enroll in the course.

Chapters

Hello and welcome to our course on exploratory multivariate data analysis. Maybe you're a student or a researcher in a scientific subject, increasingly faced with data that needs to be statistically analyzed. Or perhaps you come from industry or are simply curious to understand how to extract and understand complex data found in big tables, in subjects as diverse as surveys, sociology, biology, geography, economics, economics, the list is endless. We are going to teach you about several multidimensional data analysis methods. What they all have in common is an ability to simultaneously analyze all the variables. This can lead to a much more subtle and in-depth understanding of the data, rather than looking at the variables one by one. Another key feature of these methods is how they allow us to visualize the results. We can output plots representing the statistical individuals in the form of a cloud of points or as a hierarchical tree. We can also output plots representing the variables. The strength of these methods comes from how the individuals' and variables' visual outputs can complement each other.
Each method we present comes with real data examples, and we'll try to give an intuitive explanation of how and why each method works step by step. We're going to give you quizzes and exercises on real data so you can put the methods into practice using R, These exercises will also help you learn to interpret results from this type of methods.
At the end of the course, we hope you will be able to run these multidimensional data analysis methods on your own, and of course, be able to understand and interpret the outputs. Please join us and enroll in the course today. See you soon!