Course overview
In an increasingly data-centric world, a working understanding of data analytics and quantitative methods is essential, for all members of society. The aim of this course is to improve students' data literacy, through a largely non-technical introduction to some of the foundational concepts in statistical thinking. The course will teach students from all backgrounds how to interpret and critically appraise claims made by machine learning and quantitative data science methods, and understand both the possibilities and pitfalls of these emerging sciences. It assumes no technical background and is taught largely through case studies of applications of data science outside of academia.
Course learning outcomes
- Demonstrate the use of basic probability to solve word problems
- Critically analyse and improve data collection designs
- Compose appropriate graphics to visualise patterns in data
- Articulate the importance of statistics in modern scientific research