data description:

measures of uncertainty:

missing values:

statistical testing:

regression & correlation:

multivariate techniques:

spatial data analysis:

mean - median - mode, histograms, normality, outliers, modality,  box and whiskers plots, stem and leaf diagrams

sources of uncertainty, range, standard deviation, variance, inter-quartile range, error propagation

common problem in geology and generally ignored - real missing values vs. detection limits, and how to deal with missing values

hypotheses, confidence levels, value and rank testing, Z-, t-, Chi-squared, Kolmogorov-Smirnov, Mann-Whitney tests

Scatter diagrams, Pearson & Spearman correlation coefficients, significance of correlation, curve fitting, (non-)linear models

sum of squares methodology, discriminant function analysis, prin-ciple component & factor analysis, cluster analysis

spatial distribution of data, 3D visualization (isolines, bubble plots, trend surfaces), semi-variograms, kriging

All these aspects will be addressed both in the lectures and in practical sessions. However, it is useful to also consult the book and online resources as these provide useful background, examples and more in-depth discussion of these subjects.

Copyright:     Vincent van Hinsberg & Simon Vriend

Last updated:     March 2024

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