1. Types of data. Graphical and tabular
represantation of data. Approaches for finding unexpected in data. Exploratory data analyses
for large and high-dimensional data.
Analysis of categorical data. Elements of robust estimation. Handling missing
data. Smoothing methods. Data mining.