Statistical Data Analysis

Course content

Types of data. Graphical and tabular represantation of data. Approaches to finding the 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. Classification and Clustering applications, Application of Principle Component Analysis and Factor analysis, Use of regression trees for claasification and prediction.