Data-based business management

Bachelor

The students • know different forms of scientific knowledge acquisition and are able to formulate empirical research questions appropriately. • are able to plan and apply methodological procedures in the research process.• are able to design and apply appropriate selection, collection, processing and evaluation procedures. • know the quality criteria of quantitative and qualitative social research and are able to apply them correctly in the context of the seminar and bachelor theses to be written. • are able to structure and compile larger data sets using a spreadsheet program. • are able to analyze statistical data using a spreadsheet program. • have basic knowledge of quantitative methods in economics and basic knowledge of statistical methods and procedures for describing and analyzing economic data. • are able to apply descriptive statistics and selected test procedures.

none

Part A: Basics of scientific work: - General rules of scientific work - Ethical aspects and plagiarism / use of artificial intelligence in the research process Part B: Aspects and techniques: - Finding a research gap - Literature research (books, journals, digital library, internet) - Introduction to literature management programs - Formulating research hypotheses and questions - Citation and citation styles - Objectification of research results Part C: Content and structure of a scientific paper: - Structure of a scientific paper - Statement of problem & relevance - Presentation of the aim of the work - Structure of the table of contents - List of figures and tables - Creating a list of sources and references - Other elements of a scientific paper (affidavit, abstract, appendix, etc.) Part D: Statistics with spreadsheets: - Setting up data and spreadsheets for statistical evaluations (data entry, automatic data generation, formatting, data structures) - Application of basic arithmetic operations to statistical data (addition, subtraction, division, multiplication, powers, etc.) - Use of selected special functions (e.g. financial mathematical or statistical functions) Part E: Fundamentals of statistics - Introduction to descriptive statistics (graphical representation of data and distributions, calculation of statistical central and dispersion measures, testing for normal distribution of data) and data interpretation - Introduction to inferential statistics (difference test for nominally, ordinally and cardinally scaled data) - Introduction to correlation and factor analysis Part F: Structure of a data set and variable declaration: - Design and structure of a data set for statistical analysis using software - Determination and development of variables (dependent, independent, dummy, interaction) and scaling (nominal, ordinal, interval, cardinal) - Application of basic statistical methods using data sets The (theoretical) content is deepened through practical examples including software support.

• Bamberg, G., Baur, F., & Krapp, M. (2022). Statistik: Eine Einführung für Wirtschafts- und Sozialwissenschaftler. Berlin/Boston: Walter de Gruyter GmbH. • Braunecker, C. (2021). How to do empirische Sozialforschung: Eine Gebrauchsanleitung. Wien: Facultas Verlags- und Buchhandel AG. • Häder, M. (2019). Empirische Sozialforschung: Eine Einführung. Wiesbaden: Springer Verlag. • Schira, J. (2021). Statistische Methoden der VWL und BWL: Theorie und Praxis. München: Pearson Deutschland GmbH. • Sibbertsen, P., & Lehne, H. (2021). Statistik: Einführung für Wirtschafts- und Sozialwissenschaftler. Berlin-Heidelberg: Springer Verlag.

• Final Exam and • Quiz

German

4

25

3.5

25 % of the event is covered by eLearning. A combination between online phases (inductive method for the independent acquisition of knowledge and the practice of tasks) and presence phases (deductive method, in which assistance is given in the learning process and knowledge is imparted via frontal lectures) is used.

1

Prof. (FH) Dr. Dr. Mario Situm

FIN 1

integrated lecture

Compulsory

not applicable