Syllabus
Registration via LPIS
Day | Date | Time | Room |
---|---|---|---|
Monday | 10/14/19 | 08:00 AM - 11:00 AM | TC.1.01 OeNB |
Monday | 10/21/19 | 08:00 AM - 11:00 AM | TC.1.01 OeNB |
Monday | 10/28/19 | 08:00 AM - 11:00 AM | TC.1.01 OeNB |
Monday | 11/04/19 | 08:00 AM - 11:00 AM | TC.1.01 OeNB |
Monday | 11/11/19 | 08:00 AM - 11:00 AM | TC.1.01 OeNB |
Monday | 12/02/19 | 08:00 AM - 11:00 AM | TC.1.01 OeNB |
Monday | 12/09/19 | 08:00 AM - 11:00 AM | TC.1.01 OeNB |
Monday | 12/16/19 | 08:00 AM - 09:30 AM | TC.0.10 Audimax |
The course provides an introduction to methods and tools that support data-driven decision making in business. Beginning with basic data handling skills and progressing through statistical and operations research methods, students learn business analytics through real-world examples. A special emphasis will be put on visualization and interpretation of results.
Topics include:
- Basic Data Handling
- Basic Data Processing and Visualization
- Hypothesis Tests
- Analysis of Variance and Regression
- Exploratory Factor Analysis
- Forecasting and Simulation
- Optimization
After attending this course, students will be able to understand and apply the principles, methods and tools of business analytics to basic problems. This includes how to:
- Handle big data files in R and Excel
- Use visualization tools to identify patterns and trends
- Formulate and test hypothesis, and interpret their results in a business context
- Apply analysis of variance, regression analysis and exploratory factor analysis, and interpret the results of such analyses to support data driven decision-making in a business context
- Forecast based on historical data
- Develop and apply simulation models for decision support
- Formulate and solve a certain class of decision problems as linear programs
Attendance requirement is met if a student is present for at least 80% of the lectures.
The course is taught using a combination of lectures, class discussions, homework exercises and in-class assignments.
- Homework assignment, 30 points (6 homeworks)
- In-class assignments, 30 points
- Final exam, 40 points
In order to pass the class, you need attend at least 80 % of all classes. If you fulfill these criteria, the following grading scale will be applied:
- Excellent (1): 87.5% - 100.0%
- Good (2): 75.0% - <87.5%
- Satisfactory (3): 62.5% - <75.0%
- Sufficient (4): 50.0% - <62.5%
- Fail (5): <50.0%
For general, administrative questions, please use business-analytics-1@wu.ac.at.
For specific questions concerning certain contents, please contact the individual session-instructor directly via firstname.lastname@wu.ac.at
Please use "[Business Analytics 1] - ..." as subject to your Emails
Back