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.

4.2.3 Excalibur features

Course subject(s) Module 4. Data analysis using Excalibur and Validation

Excalibur computes the intrinsic range using the formula shown in Module 2.

However, there is no option to implement pre-specified bounds on the intrinsic range.

For example, recall Question 2 in the Dutch eating habits example. The question concerned percentages, so an obvious minimum bound is 0(%), since negative percentages do not make sense. Excalibur cannot take this restrictions automatically into account.

Hence the small differences between the information scores computed during Module 2 and the information scores in Excalibur, for the Dutch eating habits example.

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Decision Making Under Uncertainty: Introduction to Structured Expert Judgment by TU Delft OpenCourseWare is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Based on a work at https://online-learning.tudelft.nl/courses/decision-making-under-uncertainty-introduction-to-structured-expert-judgment//.
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