Class lectures and some exercise will be carried out together. Some speakers are going to be invited to discuss on advanced topics.
The course will focus on the study of univariate, bivariate and multivariate analysis using the R language, an open source environment for data management, statistical analysis, graphing and, more generally, for the use of a variety of formal methods (Networks Analysis, Time Series Analysis, Differential Equations, Machine Learning, Multivariate Statistics, etc.).
The course covers the following:
1) basic mathematical notions and logical propedeutics to computer programming;
2) operations on vectors, matrices, factors, lists, tables, data frames, using the R language;
3) read and write operations on external files using the R language;
4) graphic representations of the data using the R language;
5) programming with R: definitions of new functions, control constructs, conditional constructs and iterative constructs (if, ifelse, for, while, break, repeat, next);
6) univariate and bivariate descriptive statistics using the R language;
7) linear correlation and regression using the R language;
8) main component analysis using the R language;
9) cluster analysis using the R language;
10) network analysis using the R language;
Overview and introduction to data base management systems. Our data driven society today requires a proper approach to data management for social scientists. Our digital world today produces a huge amount of very detailed and large data logs that represent a new dimension for data scientists.
Lecturer's assignments