Content (Syllabus outline)

Statistics and computing. Coursework with statistical software R.

 

Preliminary statistical analysis. Graphical presentation, basic descriptive statistics and analysis.

 

Regression and correlation.

  • Simple linear regression model.
  • Correlation: different correlation coefficients (Pearson, Spearman, Kendall).
  • Nonlinear regression models which can be linearized.
  • Multiple regression.
  • Specific regression models in bioeconomics.

 

Multivariate statistics.

  • Distances for numerical and for categorical variables: Euclidean, Manhattan, Jaccard, itd…
  • Cluster analysis. Hierarchical methods, dendrogram. Optimization methods: Kmeans.
  • Ordination methods: classical multidimensional scaling, graphical presentation.
  • Principal component analysis.
  • An overview of other multivariate methods.

Prerequisites

Prerequisites for inclusion in study process:

Enrolment in the corresponding year of study programme.

 

Formative coursework and assessment:

Completed homeworks.

Written exam.