Principles of Data Analysis (8020551)
The following details taken from the examination regulations MSWI/15, SMPO WS 21/22 are for information purposes only and not legally binding. For legally binding information, please refer to the corresponding official examination regulations of the program Master Wirtschaftsingenieurwesen.
Key Info
Basic Information
- Studypath:
- Master Wirtschaftsingenieurwesen
- Semester:
- 2
- Course Type:
- Seminar
- Language:
- German/English
- Cycle:
- Summer term
- Scheduling:
- Entire semester
- Course Units:
- 5.0
- Credits:
- 5.0
- Course Limit:
- 18
- Erasmus Capacity:
- 0
- Compulsory Attendance:
- Yes
Lecturer
Syllabus
This course provides an introduction to statistical data analysis. This involves key concepts and definitions in data analysis and statistics.
It is composed of three parts: (1) A lecture part introducing key concepts in and methods of data analysis, their use and fields of applications. (2) An exercise part where the students train the statistical methods by means of statistical software under supervision of the lecturer. (3) An application part in that the students transfer their learning to different data sets to apply their knowledge and analyse the data.
The course covers techniques to
• describe data numerically and graphically using visualizations;
• search for structures in data (factor analysis and cluster analysis);
• test structures in data including group comparisons (t-tests and analysis of variance) and relationships (ordinary least squares regression).
Objectives
Overall goal: This course provides an overview of showcases and practices the application of the statistical techniques that are most often applied in management research.
After successfully completing this course, the students will have acquired the following learning outcomes:
Students
• … learn to choose the right quantitative research method for the research question at hand.
• … learn to understand conceptual and empirical research papers.
• … learn differences and similarities of statistical research methods.
Prerequisites
(1) Solid command of English
(2) Basic understanding of technology and innovation management
(3) Willingness to watch teaching videos online to prepare in-class session
(4) Basic statistical knowledge
Examination
The final grade can be composed as follows:
• Option A: Colloquium and presentation (50%, graded) and written examination (50%, graded, 60min.)
• Option B: Colloquium and presentation (20%, graded) and paper (80%, graded)
• Option C: Paper (50%, graded) and written examination (50%, graded, 60min.)
• Option D: Written examination (100%, graded, 60min.) or oral examination (100%, graded, 15-45min.)
The exact form of examination (A, B, C or D) will be announced at the start of the course. Unless announced differently, option B applies.
Module component for option D (if not otherwise announced at the beginning of the semester): There is also the possibility to improve grades on the voluntary submission of written exercises. For each written exercise points are awarded, depending on the extent and difficulty. The grade of the regular examination can be improved by 0.3 or 0.4 points if 1. the regular examination was passed without this improvement with a grade of 4.0 or better, and 2. if at least 80% of the possible points for written exercises were achieved.
Further Information
The lectures (Part A of the course) usually will be delivered as videos in English language.
Literature
Lecture notes and Stata Help Files
Kohler and Kreuter: Data Analysis Using Stata, Third Edition, Stata Press.