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PřF:FX003 Experiment setup and interpret - Course Information

## FX003 Experiment setup and interpretation

**Faculty of Science**

Autumn 2020

**Extent and Intensity**- 1/1. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
**Teacher(s)**- Mgr. Filip Münz, PhD. (lecturer)

Mgr. Filip Münz, PhD. (seminar tutor) **Guaranteed by**- prof. RNDr. Josef Humlíček, CSc.

Department of Condensed Matter Physics - Physics Section - Faculty of Science

Contact Person: Mgr. Filip Münz, PhD.

Supplier department: Department of Condensed Matter Physics - Physics Section - Faculty of Science **Prerequisites**-
**F7270**Math. methods for data anal.

Prerequisites for this course are general knowledge of probability and statistics (to the extent of the course F7270): manipulation with random variates, overview of basic discrete and continuous distributions, theory of estimates and hypothesis testing, linear and non-linear regression analysis. **Course Enrolment Limitations**- The course is offered to students of any study field.
**Course objectives**- Students should be (after finishing the course) capable of: - analysing statisticaly of (inhomogeneous) data sample - designing a set of proposed measurements, reveal critical points in the space of possible entry parameters - choosing and applying of a robust method of data reduction - eliminating (disentangling) trends in series of data - choosing of a suitable optimization process in model-experiment comparison
**Learning outcomes**- Students should be (upon finishing the course) capable of:

- analysing statisticaly of (inhomogeneous) data sample

- selecting of a parametric or non-parametric model function suitable for the problem in question

- designing a set of proposed measurements, reveal critical points in the space of possible entry parameters

- choosing and applying of a robust method of data reduction

- eliminating (disentangling) trends in series of data

- choosing of a suitable optimization process in model-experiment comparison

- provide correct confidence intervals for parameters even under some physical constraints **Syllabus**- Review of mathematical statistics
- Easy cases - physical experiments revisited
- Regression - from linear to orthogonal, robust methods
- Multidimensional problems, reducing number of variables
- Event densities, KDE
- Moment estimates from samples
- Orthogonal spaces (polynoms)
- Upper limits

**Literature***Statistical methods in experimental physics*. Edited by Frederick E. James. 2nd ed. Hackensack, N.J.: World Scientific, 2006. xviii, 345. ISBN 9789812705273. info

*recommended literature***Teaching methods**- Lectures combined with practical examples (during exercises), independently solved problems (sumulated "experimental" data).
**Assessment methods**- During the course, students solve individually 1-2 problems (e.g. hypothesis/model testing); final written report is based on analysis of computer-generated data, the results are discussed in a form of colloquium.
**Language of instruction**- Czech
**Further comments (probably available only in Czech)**- The course is taught annually.

The course is taught: every week.

General note: Předmět určen pro studenty Fyzikálního inženýrství VUT. **Teacher's information**- http://nymeria.physics.muni.cz/face/praxis/fdoc/mmzm/

- Enrolment Statistics (Autumn 2020, recent)
- Permalink: https://is.muni.cz/course/sci/autumn2020/FX003