This course is an introduction to statistical learning and its application to help making economic decisions. Statistical learning is the science of extracting important patterns from data, patterns that can inform a decision maker. Particularly, the course focuses on predictive analytics, the activity of predicting future events or predicting an unobserved property of an individual, a company or some other unit. The course will contain applications on business data. The students will work on those using the statistical software R. Examples of applications are statistical fraud detection and market basket analysis.
Topics
- Linear regression and classification
- Resampling methods
- Model selection
- Non-linear models
- Tree-based methods
- Unsupervised learning