KOUT 2095 - Data Science with R

This workshop is about accessing, manipulating and visualizing data with R and RStudio. You will also learn about a larger, looser set of skills and tools to work with data in general. You will be using your computer a lot throughout the course, in order to learn the R programming language and its RStudio interface. We will review some essential statistical concepts along the way, building up from exploratory data analysis to statistical modeling

Learning Outcomes
1. Proficiency in exploratory data analysis
2. Knowledge of statistical inference and modeling
3. Knowledge of the R programming language
4. Knowledge of the RStudio software
5. Exposition to current data science trends

Professional Skills
Quantitative methods, R and RStudio software, familiarity with data science.

François BRIATTE

English

- Attendance: 2 hours a week / 24 hours a semester
- Online learning activities: 12 hours a week / 24 hours a semester
- Reading and Preparation for Class: 1 hour a week / 12 hours a semester
- Research and Preparation for Group Work: 2 hours a week / 24 hours a semester
- Research and Writing for Individual Assessments: 1 hour a week / 12 hours a semester

(1) A laptop running a recent version of Windows, MacOS or Linux, with full admin privileges, in order to support the installation of the latest versions of R (r-project.org) and RStudio Desktop (posit.co/products/open-source/rstudio). (2) Minimal computing skills, e.g. unzipping files, using keyboard shortcuts, connecting to the Internet. (3) Some prior exposure to introductory statistics, e.g. descriptive statistics and association tests.

Autumn and Spring 2024-2025

Individual and group exercises, to be completed in between workshop sessions.

Feedback will be provided in class as answers to the exercises.