A loss estimate needs both a probability model and evidence from data. This topic starts by defining events, then calculates averages, spread and co-movement. It introduces the normal model and a simple regression. The goal is to calculate a result and explain its assumptions before later Programmes teach inference and model validation in depth.
By the end of this topic you should be able to:
- define events and apply the probability axioms, conditioning and independence;
- calculate expected value, variance and covariance for small distributions;
- standardise a normal random variable and interpret a normal probability;
- distinguish populations, samples, statistics and sampling uncertainty;
- fit and interpret a simple regression line without claiming causation.
In this lesson
- Contents
- The big picture
- Diagnostic use
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