In this activity you learn the topics of statistical inference and probability models which are crucial due to data variability and uncertainty, covering data as evidence for statistical inference.
Next, you consider case studies and the importance of being cautious when collecting, representing and analysing data, thinking about sampling, non-response, response biases, hidden data, survivorship bias, underestimation of risk, data misrepresentation, and how ‘noise’ and ‘outliers’ may be informative.
You have the opportunity to reflect on the data representations chosen and suggest better ways of summarising the data in the exercise that follows.