Day 1:   Introduction and univariate data       Day1.pdf

1. ‣Short Course logistics
   

2. ‣An introduction to geostatistics
   

3. ‣What are data ?
   

4. ‣Data distributions and descriptors
   

See also the following external resources;

1. Double-blind parachute testing                                external link
   

2. Try the 3-door problem yourself and win a car!        external link
   

3. Latest paper on the theory of the stork                     external link
   

4. Extensive description of the normal distribution        external link
   

5. On the construction of cumulative frequency plots    external link
   

Day 2:   QA/QC, levelling, and bivariate data       Day2.pdf

1. ‣Univariate data visualisation and comparison
   

2. ‣Data quality assessment and control
   

3. ‣Combining and levelling datasets
   

4. ‣Bivariate data and correlation
   

See also the following external resources;

1. Paper introducing the concept of violin-plots             external link
   

2. How to estimate precision from duplicates                 external link  
   

3. The GEOREM database of SRM values                      external link
   

4. Spurious correlations                                                   external link
   

Day 3:   Statistical testing       Day3.pdf

1. ‣Missing values
   

2. ‣Statistical testing, hypotheses, confidence intervals
   

3. ‣Significance of correlation coefficients
   

4. ‣Z probability testing
   

5. ‣Comparing populations in normal and robust statistics
   

6. ‣ANOVA
   

7. ‣goodness-of-fit testing
   

See also the following external resources;

1. Online calculator for Z-score probabilities                   external link
   

2. Wikipedia article on statistical testing                          external link
   

3. Online calculator for t-distribution values                     external link
   

4. Online calculator for F-distribution values                  external link
   

5. Online calculator for Chi2-distribution values             external link
   

Day 4:   Time series and regression analysis       Day4.pdf

1. ‣Systematics over time (Markov chain and randomness)
   

2. ‣Auto-correlation and cross-correlation
   

3. ‣Periodicity in time series data
   

4. ‣Linear regression models
   

5. ‣Testing regression models and assumptions
   

6. ‣Non-linear and multiple linear regression
   

7. ‣Robust regression
   

8. ‣Curve fitting
   

See also the following external resources;

1. Wikipedia article on regression analysis                    external link
   

2. The effect of uncertainty on a linear regression fit     external link
   

Day 5:   Discriminant analysis, clustering and vector methods     Day5.pdf

1. ‣Discriminant Function Analysis
   

2. ‣Hierarchical Clustering
   

3. ‣Partitioning methods, including fuzzy c-means
   

4. ‣Vector methods, PCA and FA
   

Day 6:   Discriminant analysis, clustering and vector methods     Day6.pdf

1. ‣Vector methods, PCA and FA
   

2. ‣Scree plots and varimax rotation
   

3. ‣Scores, loadings and biplot
   

4. ‣Spatial analysis of data
   

5. ‣Bubble plots
   

6. ‣Interpolation
   

7. ‣Semivariograms and kriging
   

See also the following external resources;

1. A great background resource on kriging                   external page
   

2. Wikipedia article on kriging                                        external page
   

3. QGIS, a full-featured freeware GIS program             external page
   

Copyright:     Vincent van Hinsberg & Simon Vriend

Last updated:     March 2024