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.
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.
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