![]() | Study programme 2025-2026 | Français | |
| Data Sciences I : visualisation | |||
Learning Activity |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
|---|---|---|---|---|
| S-BIOG-006 |
|
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| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Français | Français | 0 | 30 | 0 | 8 | 0 | Q1 |
Content of Learning Activity
The pedagogical material is available online: https://wp.sciviews.org. The chapters of this UE are:
- Visualisation I - Scatterplot and introduction to software & tools (Software R, RStudio, git & R Markdown/Quarto)
- Visualisation II - Histogram, density plot, violin plot
- Visualisation III - Barplot, piechart, boxplot, plots assemblage
- Data processing I - Importation, conversion, dplyr
- Data processing II - Contingency, sampling, multi-table processing with tidyr
Required Learning Resources/Tools
The content for this course is available online https://wp.sciviews.org
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
Barnier, J., 2018. Introduction à R et au tidyverse (https://juba.github.io/tidyverse/index.html). Ismay, Ch. & Kim A.Y, 2018. Moderndive: An introduction to statistical and data science via R (http://moderndive.com). Wickham, H. & Grolemund, G, 2017. R for data science (http://r4ds.had.co.nz). Cornillon, P.A. Et al, 2008. Statistiques avec R. Presses Universitaires de Rennes. 257pp. Dagnelie, P., 2007. Statistique théorique et appliquée, Volumes I et II (2ème ed.). De Boeck & Larcier, Bruxelles. 511pp (vol. I) 734pp (vol. II).
Mode of delivery
Type of Teaching Activity/Activities
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)
Location of learning activity
Location of assessment