Module label | Complex Data Analysis |
Modulkürzel | wir891 |
Credit points | 6.0 KP |
Workload | 180 h |
Institute directory | Department of Business Administration, Economics and Law (Business Administration and Business Education) |
Verwendbarkeit des Moduls |
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Zuständige Personen |
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Prerequisites | |
Skills to be acquired in this module | With successful completion of the course, students shall be able to analyze complex empirical data sets, like aggregated data, privacy constrained data, distance information, distributions, tables, symbolic or granular data. Students will also learn to handle issues of big data challenges: large number of cases or variables, unknown dependencies, redundancy, missing values, small or no variance. In this course students will learn theoretical aspects of complex data analysis, as well as practical applications for real data sets with statistical software packages. |
Module contents | Principal Component Analysis, Correspondence Analysis, Cluster Analysis, Linear Discriminant Analysis, Multidimensional Scaling, CART, Symbolic Data Analysis |
Literaturempfehlungen | Billard, L. and Diday, E. (2006): Symbolic Data Analysis, West Sussex Hastie, T., Tibshirani, R. and Friedman, J. (2001): The Elements of Statistical Learning, New York Pedrycz, W. (2017): Granular Computing, Boca Raton Tuffery, S. (2011): Data Mining and Statistics for Decision Making, West Sussex |
Links | |
Languages of instruction | German, English |
Duration (semesters) | 1 Semester |
Module frequency | |
Module capacity | unlimited |
Modullevel / module level | |
Modulart / typ of module | |
Lehr-/Lernform / Teaching/Learning method | |
Vorkenntnisse / Previous knowledge |
Form of instruction | Comment | SWS | Frequency | Workload of compulsory attendance |
---|---|---|---|---|
Lecture | 2 | SoSe oder WiSe | 28 | |
Seminar | 2 | SoSe oder WiSe | 28 | |
Präsenzzeit Modul insgesamt | 56 h |
Examination | Prüfungszeiten | Type of examination |
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Final exam of module | Am Ende der Vorlesungszeit |
Klausur oder Mündliche Prüfung oder Hausarbeit oder Referat |