Exploratory data analysis with R – ONLINE

Exploratory data analysis with R – ONLINE

  • First day
    1:00 pm - 4:00 pm
  • Second day
    1:00 pm - 4:00 pm
  • Third day
    1:00 pm - 4:00 pm

Course details

statistics course | level: beginner | register now
for questions related to this event, contact kuleuven@flames-statistics.com
affiliation: KU Leuven


Exploratory data analysis or “EDA" is an important step in analyzing your data. Generally speaking, any method of looking at data that does not include formal statistical modeling and inference falls under the term “exploratory data analysis”.

Exploratory data analysis can be classified in two methods. First, each method is either non-graphical or graphical. Second, each method is either univariate or multivariate (usually just bivariate). In this course, we are going to focus on:

Univariate non-graphical EDA
• Categorical and quantitative data overview
• Central tendency
• Spread
• Skewness and kurtosis

Univariate graphical EDA
• Histograms
• Boxplots
• Quantile normal plots

Multivariate non-graphical EDA
• Cross-tabulation
• Correlation, covariance & correlation matrix

Multivariate graphical EDA
• Univariate graphs by category
• Scatterplots

In the more hands-on part of the course, we will run through an informal “checklist” of things to do when embarking on an exploratory data analysis using R & RStudio. Several examples and applications in R will be explained and you will have time to practice on your data.


This course is NOT and introductory courses to R. This means that you MUST already know how to code in R.

The course is intended for beginners with little or no experience with statistics.

Background readings


PhDs and postdocs of a Flemish university: 0 €
Other academics: 90 €
Non-profit/Social sector: 150 €
Private sector: 300 €




Cristina Cametti

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