- EBA 3500
- 7.5 Credits
The students will learn the most important techniques in applied statistics and data analysis, with an emphasis on linear regression and logistic regression. Students are given hands-on experience with data analysis projects, and will gain further knowledge in working with data, using descriptive statistics to motivate models, and using models to turn data into actionable knowledge. Data examples and applications will be given.
The following topics will be covered using Python as statistical analysis system.
- Python programming using packages such Numpy, Scipy, statsmodels, Pandas, and matplotlib.
- Data visualization with matplotlib.
- Basic data manipulation using Pandas and numpy.
- How to make simple simulation studies.
- Multiple linear regression in statsmodels.
- Logistic regression in statsmodels.
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