The ability to competently handle data sets and analytic tools is a key attribute of the professional data analyst. Underlying this ability is a solid grounding in statistics that allows data analysts to successfully interact with various methods of testing, interpretation and validation.

This module will give you an introduction to the relevant mathematical and statistical tools. You will also learn the techniques necessary for data analysis as well performing correctives thereon.

At the end of this module students are able to purposefully select and implement data collection and pre-processing methods (error analysis and correction). They can correctly identify the advantages and drawbacks of these processes and describe their implications for further processing.

Univariate and multivariate methods can be differentiated from one another, and their processes and applications can be explained. Students have developed the methodological and mathematical knowledge required for the preparation and analysis of data sets.

Students are able to use professional software to solve statistical problems and generate concrete answers based on given data. For this purpose, they can independently create, test and use scripts of low to medium complexity. When performing such tasks, they are aware of the key fundamental principles of error-free and transparent programming. They understand the structure of more complex scripts and can interpret individual commands.

• Teamwork assignment (50%)  

• Written examination (40%) 

• Mid-term exam (10%)