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

Séminaire

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: 1 hour a week / 12 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. The laptop must be able to run the latest versions of R (r-project.org) and RStudio Desktop (rstudio.com). (2) Minimal computing skills, e.g. unzipping files. (3) Some prior exposure to introductory statistics, e.g. descriptive stats and association tests.

Spring 2022-2023

Individual and group exercises, to be completed in between workshop sessions, and possibly group projects to be elaborated throughout the semester.

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