Critical Thinking with Data (MAST20034)

This subject teaches students to become critical interpreters and users of data-based evidence. Future data scientists working across many disciplines will develop skills in identifying the strengths and weaknesses of arguments based on quantitative evidence, and learn to evaluate reasoning that uses probabilistic ideas and the results of statistical analysis.  They will develop skills in interpretation, principled reporting and communication of statistical evidence.

Data-based evidence is foundational in all of science.  The growth of “big data” and interest in data science has accentuated the need for a well-developed understanding of how scientific studies are designed, analysed and communicated.  The media, other academic research and many aspects of everyday life also use and build on data presented and processed in many different ways.

The subject examines methods of judging the quality of data-based evidence, and the strength of conclusions drawn from it, including concerns in establishing causality. It provides students with frameworks for evaluating study quality and deals with quantifying uncertainty in conclusions, describing how data-based evidence can contribute to the accumulation of scientific knowledge.  

The subject emphasises the skills needed to use, interpret and communicate statistical and data science related ideas and findings in real world contexts.