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Softwares and methods of statistical exploratory data analysis


At the end of this module, the student will have understood and be able to explain (main concepts) :
- Data base organisation of SAS tables and R data frames. Syntax of
main SAS procedures and R language. SAS macros or R function design, program
and test; Statistical analysis of multidimensional data: dimension reduction and
clustering depending on the categories of statistical variables);
- Statistical interpretation of various graphical displays including
the different kinds of factor analyses and clustering.
The student will be able to:
- manage massive data bases with statistical software - SAS and R (GNU-license)
- write SAS and R programs to perform classic statistical estimation;
- perform an exploratory data analysis of real data frames with univariate,
bivariate and multivariate methods featuring PCA, MCA, FDA , kmeans,
depending on data structures.
- detect relevant structures within complex data sets and compile insightful

Form of assessment

The evaluation of outcome prior learning is made as a continuous training during the semester. According ot the teaching, the assessment will be different: as a written exam, an oral exam, a record, a written report, peers review...