Important announcement

Dear visitor,

Please note that this OpenCourseWare platform will be replaced at the end of 2026 by a new platform (under the same url ocw.tudelft.nl).

Courses and their contents that are currently available the platform will partly be migrated. URL’s for this content will change and content might be unavailable for some time. In addition, some courses will not be available anymore.

If you are linking to specific courses on this platform (for instance for your students), please take timely measures to avoid problems with access. Possible actions are:

  • Download the materials to your local platform (laptop, server)
  • For educators only (including TU Delft lecturers): Contact us at ocw@tudelft.nl and inform us what course you are using in what context (institute, program, period of use, number of students). We will research (in collaboration with the authors of the course) and decide if we will migrate the course, and if yes, can supply you with a new url.

Thank you.

Learning objectives

Course subject(s) 1. Introduction to Observation Theory

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
Creative Commons License
Observation Theory: Estimating the Unknown by TU Delft OpenCourseWare is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Based on a work at https://ocw.tudelft.nl/courses/observation-theory-estimating-unknown.
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