Prof. Christian Martin Hennig

Argomenti del programma: Random sampling and sampling distributions. Central limit theorem. Estimation theory. Point estimation: finite sample and asymptotic estimator properties Confidence intervals. Statistical hypothesis tests and their logic and interpretation. The concept of p-values. Tests for many standard problems including the mean, proportion, two sample comparison, categorical data. Issues with and criticism of tests.

Argomenti del programma: The course will confront the student with a number of case studies covering different areas such as missing values, modelling, regression and related methods, data visualisation, analysis of ordinal and categorical data.

Argomenti del programma: Cluster analysis: k-means, construction of distances, hierarchical clustering, partitioning around medoids, average silhouette width, mixture models, with algorithms, R-coding, theory, applications and in-depth discussion; advances techniques of cluster analysis; outlook on big data issues Robust statistics: Influence function, breakdown point, robust estimation of univariate and multivariate location and scale and…