DATA ANALYSIS FOR BUSINESS

Provide students with practical skills to work with and summarize datasets, aiming to provide business insights.

The courses “Statistics” (https://www.luiss.edu/cattedreonline/corso/BA06/C/L25BABASE/2025) and “Applied Business Statistics” (https://www.luiss.it/cattedreonline/corso/BA012/A/L21BABASE/2025) are mandatory prerequisites for this course (first and second year of the degree in Business Administration, respectively). Also, basic Python programming is required.

The students will have a great ability to use statistics to provide business insights. Also, the continuous assessment program will enhance the student's skills in Python.

Python brief recap; Principal Component Analysis; Panel data regression; Univariate time series models; Basic of Machine Learning.

[SW] Stock, J.H. and Watson, M.V. (2020), Introduction to Econometrics, 4th edition (or earlier), Pearson [ISL] James, G., Witten, D., Hastie, T., Tibshirani, R., and Taylor, J. (2023), An Introduction to Statistical Learning with Python, Springer [HA] Hyndman, R.J., Athanasopoulos, G., Garza, A., Challu, C., Mergenthaler, M. and Olivares, K.G. (2026), Forecasting: Principles and Practice, the Pythonic way, freely available online at: https://otexts.org/fpppy/ Course material

Theory + Practical classes.

Midterm test (30%, written) + Group project (40%, oral presentation) + Final exam (30%, written)

TBD