G3101k Basics of geological data treatment

Faculty of Science
Autumn 2023
Extent and Intensity
1/2/0. 4 credit(s). Type of Completion: zk (examination).
Teacher(s)
Mgr. Renata Čopjaková, Ph.D. (lecturer)
Zbyněk Cincibus (assistant)
Petra Ludvová Hašková, DiS. (assistant)
Guaranteed by
Mgr. Renata Čopjaková, Ph.D.
Department of Geological Sciences – Earth Sciences Section – Faculty of Science
Contact Person: Ing. Jana Pechmannová
Supplier department: Department of Geological Sciences – Earth Sciences Section – Faculty of Science
Timetable
Fri 13. 10. 10:00–12:00 Gp,02006, Fri 3. 11. 9:00–13:00 Gp,02006, Fri 1. 12. 9:00–10:00 Gp,02006
Prerequisites
! G3100 Geological Data Treatment && !( G3101 Geological Data Treatment ) && !NOW( G3101 Geological Data Treatment ) && ( (!(PROGRAM(B-GE)||PROGRAM(N-GE)||PROGRAM(D-GE4)||PROGRAM(D-GE)||PROGRAM(C-CV))) || (NOW( G0101 Occupational healt and safety )&&NOW( C7777 Handling chemical substances )))
Knowledge of mathematics on secondary school level
Course Enrolment Limitations
The course is only offered to the students of the study fields 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
The curriculum is focused on the acquisition of theoretical background to statistical analysis of numerical data in geosciences and their practical treatment using Microsoft Excel. The students are acquainted with principles of probability, descriptive (exploratory)statistics, statistical inference, parametric and non-parametric testing of hypotheses, characterisation of multidimensional datasets by regression and correlation analysis, time-series analysis, multivariate methods of statistical analysis (cluster, discriminant, factor etc.).
Learning outcomes
Student will be able to use basic mathematical methods on geological data and will be able to interpret them after completing the course.
Syllabus
  • 1. Introduction. Teach-in. The notion of data, types of geological data. Stages of data analysis: Data acquisition; analysis and choice of data. Formalisation (codification and standardization) of data. Data recording and classification. Exploratory data analysis, graphical presentation, types of graphs used in geosciences. Factual interpretation and formulation of results.

    2. History and the present of statistics. Examples of usage of statistics in geology. Basic statistical terms: statistical unit, statistical variable (qualitative/ quantitative; ordinal; continuous / discrete; alternative), statistical population (unidimensional, multidimensional). Definition of probability, random variable.

    3. Description of univariate data. Random sampling. Distribution of data in the population - frequency distribution. Frequency - absolute, relative, cumulative. Graphing the frequency distribution; probability paper.

    4. Basic statistical parameters Median, quantiles, mode, range. Moments: arithmetic mean, variance, standard deviation, coefficient of variation), skewness, kurtosis. Geometrical mean. Harmonical mean.

    5. Basic types of frequency distributions. Distributions - normal, log-normal, binomial aand Poisson, special types (t-, F, chi square distributions). Examples of geological phenomena and their frequency distributions. Statistical inference. Estimates of the parameters of population. Properties of estimates, consistence, accuracy, robustness.

    6. Testing statistical hypotheses Basic terms and testing procedures. Errors of the first and second type. Goodness of fit tests, test of variance, significance tests of difference between means. Paired tests. Identification of outliers. Analysis of variance(one-way, two-way). Non-parametrical testing (test for randomness, Wilcoxon test, Mann-Whitney test)

    7. Statistical description of relations between variables. Correlation analysis. Regression analysis (simple linear correlation, nonlinear correlation, multiple correlation.

    8. Multivariate statistical methods. Discriminant analysis. Cluster analysis (hierarchical, nonhierarchical methods, fuzzy clustering). Factor analysis, principle components method.

Literature
    recommended literature
  • ZVÁRA, Karel. Biostatistika. 1. vyd. Praha: Karolinum, 1998, 210 s. ISBN 8071847739. info
  • Statistické zpracování experimentálních dat :v chonometrii, biometrii, ekonometrii a v dalších oborech přírodních , technických a společenských věd. Edited by Milan Meloun. 2. vyd. Praha: East Publishing, 1998, xxi, 839 s. ISBN 80-7219-003-2. info
  • LEPŠ, Jan. Biostatistika. Vyd. 1. České Budějovice: Jihočeská universita, 1996, 165 s. ISBN 8070401540. info
  • BRÁZDIL, Rudolf. Statistické metody v geografii : cvičení. 3. vyd. Brno: Vydavatelství Masarykovy univerzity, 1995, 177 s. ISBN 8021012609. info
  • HANOUSEK, Jan and Pavel CHARAMZA. Moderní metody zpracování dat :matematická statistika pro každého. 1. vyd. Praha: Grada, 1992, 210 s. ISBN 80-85623-31-5. info
  • SATTRAN, Vladimír and Blahomil SOUKUP. Použití matematických metod v geologii. Vyd. 1. Praha: Ústřední ústav geologický v Academii, 1973, 153 s. info
Teaching methods
lectures and theoretical training, statistical functions in the Excel
Assessment methods
The final test of theoretical and practical knowledge (Excel)
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: Bude otevřeno v podzimním semestru 2023/2024.
The course is also listed under the following terms Autumn 2011, Autumn 2013, Autumn 2015, Autumn 2019, autumn 2021.
  • Enrolment Statistics (recent)
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