These resources form part of a course developed and run by Mine Çetinkaya-Rundel and David Elliott of the University of Edinburgh’s School of Mathematics.

Learn to explore, visualize, and analyze data to understand natural phenomena, investigate patterns, model outcomes, and make predictions, and do so in a reproducible and shareable manner. Gain experience in data collection, wrangling, and visualization, exploratory data analysis, predictive modeling, and effective communication of results while working on problems and case studies inspired by and based on real-world questions. The course will focus on the R statistical computing language. No statistical or computing background is necessary.

You can access course materials and videos from the links below.

Course materials: https://www.introds.org/ (licensed CC BY SA 4.0)

Course videos: https://media.ed.ac.uk/channel/IDS%202020/ (licensed CC BY NC SA)

Header image: Image by Денис Марчук from Pixabay