Practical Analysis of Data and Risks

The course is not on the list Without time-table
Code Completion Credits Range
16PADR KZ 4 1P+3C
Garant předmětu:
Department of Dosimetry and Application of Ionizing Radiation

The aim of the course is to provide students with a summary of basic theoretical knowledge, especially in the field of probability and statistics, useful for data and risk analysis. The main content of the course is practical application of theoretical procedures, especially data analysis using available software solution. Students will learn to perform comprehensive analysis and evaluation of data and risks.

Syllabus of lectures:

1.Introduction to data processing, uncertainties of measurement and data processing, classification of phenomena contributing to the uncertainty of results, quantification of uncertainties

2.Basic statistical data processing and exploratory analysis of one-dimensional data - description and properties of a one-dimensional data set, verification of assumptions about the data set, statistical analysis of data

3.Selection methods, basic statistical distributions, the transformation of date, point and interval estimation, confidence intervals

4.Linear regression models, correlation, nonlinear regression models

5.Statistical hypothesis testing, analysis of variance, correlation analysis

6.Descriptive statistics of multidimensional data and expoloratory analysis, basic statistical analysis of multidimensional data

7.Classical interpolation techniques, spline interpolation, approximation by function and polynomial, data smoothing

8.Risk analysis, risk assessment and planning of activities to prevent and eliminate risks

Syllabus of tutorials:

1.Basic data description, representative data and graphical presentation of experimental data

2.SW for statistical data processing and visualization

3.Graphical processing and presentation of data, demonstration of available SW with a focus on open-source SW

4.Basic statistical processing and analysis of data in R-software

5.Graphical visualization of data in R-software

6.Testing of data normality, transformation of data, calculation of basic statistics

7.Graphical visualization of data in dependence on the geographical position - application QGIS software

8.Calibration - calibration of experimental data

9.Approximation and interpolation of one-dimensional data

10.Approximation and interpolation of multi-dimensional data

11.Practice in identification and description of risks, identification of risk sources

12.Practise in qualitative and quantitative risk analysis, estimation of the probability of threats

13.Comprehensive risk assessment and analysis of consequences

14.Processing of selected data set with graphical output - individual work

15.Risk analysis for the model situation - individual work

Study Objective:
Study materials:

Key References:

[1] M. J. Crawley. The R Book. WILEY 2013.

[2] M. J. Crawley. Statistics: An Introduction Using R. WILEY 2015.

Recommended References:

[3]A. Fiels, J. Miles, Z. Field: Discovering Statistics using R, SAGE Publications Ltd. 2012

Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2024-06-16
Aktualizace výše uvedených informací naleznete na adrese https://bilakniha.cvut.cz/en/predmet6776106.html