ABSTRACT
How do statisticians deal with uncertainty? Well, we eat it up. It’s our bread and butter. All our formal training is geared towards giving us tools with which to quantify numerical uncertainty, starting with probability theory and progressing through distribution theory and becoming familiar with the properties of statistical parameters such as means, medians and standard deviations. We cannot avoid learning about hypothesis testing and inference, regression modelling and goodness of fit. A well-rounded statistician will also have studied survey sampling, experimental design and multivariate analysis. A recent statistics graduate will almost certainly have studied units in data mining, Bayesian analysis and bootstrapping.
