Dr. Maxime Walder

Applied Methods

The class _Applied Methods_ aims to introduce students to the use of data and statistics to answers substantial questions and provide student with a strong and practical background in the analysis and visualisation of data with R. In addition to the classical statistical approach, the class is designed to provide an fundamental transferable skill to the use of data for data-driven report and in-depth analyses with quantitative data.

The course first covers the basics of R and RStudio, on statistics and data manipulation.

Second, the course dives into the data vizualisation and the production of high quality and resolution figures.

Third, the class then turns on more complexe analyses with sessions on regression models, interaction terms, and their associated visualization.

Fourth, the class then provide key technical skkils on how to use R to create data driven reports, and create interactive data leaderbord.

Finally, the course ends with a introduction to quantitative text analyses, text data pre-processing, text statistics and the visualization of text data.

Overall, this course is designed to provide a strong practical guide to use quantitative data and produce data-driven transferable knowledge.

For more information, you can download the full syllabus here: ↓ Download

Here is a table with the summary for each session:

Session Date Title Material
1 September 18 Introduction to R and RStudio ↓ Download
2 September 25 Data manipulation and descriptive statistics ↓ Download
3 October 2 Data visualization ↓ Download
- October 9 Dies Academic
4 October 16 Assignment 1
Writing report with Quarto
↓ Download
5 October 23 Hypothesis testing and introduction to regressions ↓ Download
6 October 30 Interpret interaction terms in statistical models ↓ Download
- November 6 Reading week
7 November 13 Assignment 2
Free code session on projects
↓ Download
8 November 20 Introduction to text as data ↓ Download
9 November 27 Introduction to ShinyR: Building shiny applications ↓ Download
10 December 4 Assignment 3
Introduction to Webscrapping
↓ Download
11 December 11 Group project presentations 2
Using Application Private Interfaces (API)
↓ Download
12 December 18 Group project presentations 3
Class synthesis
↓ Download

Contact

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