G3991 Experimental data analysis

Faculty of Science
Autumn 2020
Extent and Intensity
1/0. 1 credit(s). Type of Completion: z (credit).
Taught online.
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.
  • Brandt, Siegmund, 2014. Data Analysis (Fourth Edition), pp. 523, Springer, Berlin.
  • StatSoft (2017): Elektronická učebnice statistiky. - On-line: http://www.statsoft.cz/podpora/elektronicka-ucebnice-statistiky.
  • Jay L. Devore, Kenneth N. Berk, Matthew A. Carlton, 2021. Modern Mathematical Statistics with Applications (Springer Texts in Statistics) 3rd ed., pp. 988,‎ Springer. ISBN-13: 978-3030551551, ISBN-10: 3030551555.
Teaching methods
A distance learning: The individual study of the teaching materials supplemented by comments.
Assessment methods
written test In the case of a crisis pandemic situation, the course will be completed in the autumn semester of 2020 by distance form.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught once in two years.
Information on the per-term frequency of the course: Bude otevřen v podzimním semestru 2020/2021.
The course is taught: in blocks.
The course is also listed under the following terms Autumn 2014, Autumn 2016, Autumn 2018.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2020/G3991