PřF:G3101k Geological Data Treatment - Course Information

G3101k Basics of geological data treatment

Extent and Intensity

1/2/0. 4 credit(s). Type of Completion: zk (examination).

Teacher(s)

Mgr. Renata Čopjaková, Ph.D. (lecturer)

Guaranteed by

Mgr. Renata Čopjaková, Ph.D.
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

Timetable

Fri 11. 10. 13:00–15:00 Gp,02006, Fri 8. 11. 11:00–16:00 Gp,02006, Fri 3. 1. 10:00–11:00 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 chemicals )))
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)

The course can also be completed outside the examination period.
Information on the per-term frequency of the course: Bude otevřen v podzimním semestru 2019/2020.

• Enrolment Statistics (Autumn 2019, recent)
  
• Permalink: https://is.muni.cz/course/sci/autumn2019/G3101k