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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2018/2019

Statistical data analysis

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Code Completion Credits Range
02SSD Z,ZK 4 2+2
Lecturer:
Olga Rusňáková (guarantor), Miroslav Myška
Tutor:
Miroslav Myška
Supervisor:
Department of Physics
Synopsis:

The course is primarily focussed on practical application of methods of experimental data analysis. Students obtain knowledge of different statistical methods and their usage, fitting methods, and testing of hypothesis.

Requirements:

Knowledge of basic course of probability and statistics.

Syllabus of lectures:

1. Basic concepts of mathematical statistics I.

2. Basic concepts of mathematical statistics II.

3. Main statistics for experiment.

4. Estimates of unknown parameters.

5. The method of least squares.

6. The band of reliability.

7. Numerical instability and its solution.

8. Iteration methods for finding the least square.

9. The maximum likelihood method.

10. Methods for generating random samples.

11. Monte Carlo method.

12. Statistical hypotheses and their testing.

13. Examples of testing of hypothesis.

Syllabus of tutorials:

1. Basic concepts of mathematical statistics I.

2. Basic concepts of mathematical statistics II.

3. Main statistics for experiment.

4. Estimates of unknown parameters.

5. The method of least squares.

6. The band of reliability.

7. Numerical instability and its solution.

8. Iteration methods for finding the least square.

9. The maximum likelihood method.

10. Methods for generating random samples.

11. Monte Carlo method.

12. Statistical hypotheses and their testing.

13. Examples of testing of hypothesis.

Study Objective:

Knowledge:

Calculations of statistical variables, agreement tests, chi squared, statistical models and tests of hypotheses

Abilities:

Use of basic methods of data analysis, data fiting, decisions using statistical variables

Study materials:

Key references:

[1] T. Eadie et al., Statistical Methods in Experimental Physics, Amsterdam,1971.

Recommended references:

[2] G. Cowan, Statistical Data Analysis, Clarendon Press, Oxford, 1998.

[3] D.S. Silva, Data Analysis A Bayesian Tutorial, Claredon Press, Oxford, 1998

Note:
Time-table for winter semester 2018/2019:
Time-table is not available yet
Time-table for summer semester 2018/2019:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2019-03-20
For updated information see http://bilakniha.cvut.cz/en/predmet2826806.html