PřF:G3991 Experimental data analysis - Course Information
G3991 Experimental data analysis
Faculty of ScienceAutumn 2018
- Extent and Intensity
- 1/0/0. 1 credit(s). Type of Completion: z (credit).
- Teacher(s)
- doc. Ing. Jiří Faimon, Dr. (lecturer)
- Guaranteed by
- doc. Ing. Jiří Faimon, Dr.
Department of Geological Sciences – Earth Sciences Section – Faculty of Science
Contact Person: doc. Mgr. Martin Ivanov, Dr.
Supplier department: Department of Geological Sciences – Earth Sciences Section – Faculty of Science - Prerequisites (in Czech)
- ( (!(PROGRAM(B-GE)||PROGRAM(N-GE)||PROGRAM(D-GE4)||PROGRAM(D-GE)||PROGRAM(C-CV))) || (NOW( G0101 Occupational healt and safety )&&NOW( C7777 Handling chemicals )))
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 32 fields of study the course is directly associated with, display
- Course objectives
- To summarize and deepen the knowledge of students in the field of data analysis with a focus on correlation analysis and regression analysis in solving geological problems.
- Learning outcomes
- Student will be able:
- to process and edit data files
- to convert raw data into equidistant data
- to recognize and eliminate trends (convert to stationary data)
- to segment data into statistically homogeneous sections
- to perform a correlation analysis of individual variables
- to determine dependencies by regression analysis - Syllabus
- 1. Quantitative and qualitative sciences: The position of geology in the natural sciences.
- 2. Geological data: Numeric data, data acquisition, data analysis, IT role.
- 3. Dependencies, functions, variables. Mathematical variable, linear and nonlinear functions. Dependent and independent variable. Random Variable. Normal data layout.
- 4. Spatial and time series. Data step, equidistant data.
- 5. Trends, seasonality: Interpolation, extrapolation, pitfalls. Annual, diurnal seasonality.
- 6. Correlation analysis of geological data: Stationary data. Positive, negative correlation, correlation force, correlation coefficient, test results. Multiple variables - correlation matrix. Non-parametric correlation.
- 7. Hidden variable, multi-collinarity of variables: Problems of interpretation of correlation results.
- 8. Cross-correlation, autocorrelation: Time shifts and delay dependent variables. Periodicity depending.
- 9. Regression analysis of geological data: Function selection, tests. Least squares method, function minimization, numerical methods. Coefficient of determination R.
- 10. Non-linear regression: phenomenological and model dependency, polynomial regression and exponential function.
- 11. Multiple regression: Determination of dependence of multiple variables, descending and ascending regression.
- 12. Segmentation of data: Entropy of curves, statistical homogeneity and non-homogeneity of data series, series segmentation.
- Literature
- recommended literature
- Davis J.C. (2002): Statistics and data analysis in geology (third edition). John Wiley & Sons. New York, pp 638.
- not specified
- StatSoft (2017): Elektronická učebnice statistiky. - On-line: http://www.statsoft.cz/podpora/elektronicka-ucebnice-statistiky.
- Teaching methods
- lectures
- Assessment methods
- written test
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- The course is taught once in two years.
Information on the per-term frequency of the course: Bude otevřen v podzimním semestru 2018/2019.
The course is taught: in blocks.
- Enrolment Statistics (Autumn 2018, recent)
- Permalink: https://is.muni.cz/course/sci/autumn2018/G3991