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Code: 44013
ECTS: 4.0
Lecturers in charge: prof. dr. sc. Gordana Medunić
Lecturers: prof. dr. sc. Gordana Medunić - Exercises
Take exam: Studomat
English level:


All teaching activities in the course will be held on English. This level includes courses with multiple groups (i.e., all teaching will be held strictly in Croatian for Croatian groups, and strictly in English for English groups).

1. komponenta

Lecture typeTotal
Lectures 30
Exercises 15
* Load is given in academic hour (1 academic hour = 45 minutes)
Basic concepts in statistics: relevance of geostatistics, measuring scales. Definition of a set of data: population, sample, sampling frame, problems with geochemical data (censored values, outliers). Theory of probability: basic concepts (probability laws, Bayes's theorem, conditional probability).Measures of central tendency: arithmetic mean, mode, median, quantiles. Measures of variability: range of variation, interquartile, mean deviation, variance, standard deviation, coefficient of variation. Testing normal populations: central limits theorem, Shapiro-Wilk W test. Correlation analysis: Pearson's coefficient of correlation, simple and multiple linear correlation, partial correlation, rank correlation coefficients. Regression analysis: simple and multiple regression, scatter diagram, least-squares method, regression diagnostics. Sampling design: a concept and size of a sample, a hierarchical sampling design based on an unbalanced sampling scheme. Analysis of variance: F-test, post-hoc tests (Scheffe, HSD for unequal N). R-mode factor analysis: vector space model, problem of the number of possible factors, interpretation of factor loadings' joint behaviour towards variables. Cluster analysis: R-mode (classification of variables) and Q-mode (classification of samples) based on hierarchical clustering, construction of dendrogram. Formulating conclusions in statistics: accepting or rejecting of null-hypothesis, level of significance. Parametric and nonparametric statistics: Wald-Wolfowitz, Kolmogorov-Smirnov and Mann-Whitney U tests.

Learning outcomes:

Knowledge and understanding the spatial variations of geological features on the basis of the quantitative methods of analysis of geological data.
Ability to recognise the models and structures in population on the basis of available samples. Ability to interprete geological phenomena.
Ability to devise the sampling procedures.
  1. Petz, B. (2004) : Osnovne statističke metode za nematematičare. Naklada Slap, Jastrebarsko, 384 str.
  2. Šošić, I. i Serdar, V. (1995) : Uvod u statistiku. Školska knjiga, Zagreb, 363 str.
2. semester
Mandatory course - Regular study - Environmental Geology
Mandatory course - Regular study - Geology
Mandatory course - Regular study - Geology
Consultations schedule: