project 03 of 04
Global Superstore Analysis
An end-to-end statistical deep dive into a retail dataset.
- Role
- Team member
- Type
- Course team project
- Focus
- Statistics in Python
What it is
We took the Global Superstore retail dataset and asked it everything a statistics course could throw at it, from how the numbers are distributed to what actually predicts the outcomes.
What I did
- Distribution fitting and maximum likelihood estimation (MLE).
- Hypothesis testing, ANOVA and MANOVA.
- Bayesian inference.
- Regression: OLS, Ridge/Lasso and logistic regression.
Built with
- Python
- Pandas
- NumPy
- Statistics
- scikit-learn