Course MA7BY020: Exploratory Data Analysis is an introduction to the principles and practice of data exploration and visualization using the R programming language. Keeping an eye on Machine Learning and Data Science, the course will cover the following topics:
- Tabular data manipulation
- Data visualization
- Univariate and bivariate analysis for qualitative and quantitative data
- Multivariate analysis starting with multiple linear
- Matrix methods based on Singular Value Decomposition: PCA, CA, CCA, …
- Clustering methods
After that course, you will be able to:
- Handle tabular data using R version of the relational algebra (
dplyr) - Visualize data using
ggplot2andplotly - Perform univariate and bivariate analysis, compute and assess statistical summaries
- Perform multivariate analysis using matrix methods
- Diagnose and validate the results of multivariate analysis
- Perform, discuss and communicate the results of SVD factorization methods
- Perform, discuss and communicate the results of clustering methods
- Communicate the results of the analysis in a clear and concise manner using Quarto reports, presentations, and dashboards
The course is based on the R programming language, the RStudio IDE, and the VS Code Ide. We will rely on the tidyverse package and attempt to take advantage of R tidy evaluation mechanisms to write expressive and efficient code.
We will use the quarto package for reproducible research.