Bayesian statistics
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1 . Mapping with R
Following the first session about mapping with R I would like to propose you two exercises:
1) Plot a map of the world that presents information on the number of earthquakes around the world (by country)

Hint: The Significant Earthquake Database contains information on destructive earthquakes from 2150 B.C. to the present
2) Plot a map of Spain that shows any socio-economic variable by province (eg. population)

Hint:  You can find Spanish map files and data at Instituto Nacional de Estadística.
2. Data mining
After reading Development of Arab Water Sustainability Index …

The final project for the Advanced Quantitative Data Analysis course consists in a multidimensional analysis of nuclear energy around the world. Some question you may try to ask are:

is it safe?
is it clean?
is it cheap?
is it fair?

You may find inspiration for a discussed analysis in the Statistical Analysis and Visualization of the Drug War in Mexico by Diego Valle.
Some useful links:
Nuclear power plant accidents: listed and ranked since 1952
Nuclear energy data
The Nuclear Energy Agency’s annual brown book

pc.cr <- princomp(USArrests, cor = TRUE)
summary(pc.cr)
loadings(pc.cr) ## note that blank entries are small but not zero
plot(pc.cr) # shows a screeplot.
biplot(pc.cr)

[\code]
Clustering

View more presentations from Alberto Labarga.

Readings:
Measuring environmental degradation by using principal component analysis
Development of Arab Water Sustainability Index Using Principal Component Analysis
A MULTIVARIATE ANALYSIS OF THE HUMAN DEVELOPMENT INDEX