Statistical data analysis
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:
 Timetable for winter semester 2018/2019:
 Timetable is not available yet
 Timetable for summer semester 2018/2019:
 Timetable is not available yet
 The course is a part of the following study plans:

 Experimentální jaderná a částicová fyzika (elective course)