In this module we will introduce to you what “estimation” is and explain when you need it. You will learn about the generic sources of uncertainty in observations, and the concepts that you need later on, e.g. deterministic vs. stochastic parameters, random vs. systematic errors, precision vs. accuracy, bias, and the probability distribution function as a metric of randomness. All the concepts are explained by various practical examples.

Learning objectives

In this module you will learn to …

• … distinguish different types of uncertainties / errors
• … understand the concepts of precision and accuracy
• … carry out a decomposition in knowns/unknowns/observations, deterministic/stochastic