Legal Analytics
Full course description
The world is increasingly dominated by information technology and data. Economic and social relations are digitized. Technological innovation is already disrupting the practice of law and the legal professions. In Legal Analytics, you will learn how to use legal information as data and apply quantitative methods to law. The computational approach to law of this course provides an understanding about how data science techniques can help improve our understanding of the law and may help design innovative legal services and legal solutions.
In this course, you will learn about the following major topics:
- Introduction to Legal Analytics
- Quantitative Research Design
- Data and the Data Science Pipeline
- Exploratory Data Analysis
- Visualization
- Statistical Inference
Teaching methods
Lectures and tutorials. Online courses in DataCamp Academic will be used for learning Python.
Course objectives
Upon completion of the course, a student is able to:
- Explain and apply fundamental concepts and principles of data-driven research;
- Explain and apply fundamental concepts of statistics and data science;
- Clean and manipulate a dataset in Python;
- Perform quantitative and visual exploratory (legal) data analysis in Python
- Communicate (written and oral) and visualize (legal) data and results.
Prerequisites
None. This course is intended for students without any statistics or computer programming experience.
Recommended reading
- Epstein L & Martin AD (2014). An Introduction to Empirical Legal Research. Oxford: OUP. http://empiricallegalresearch.org
- Kelleher, J. D., & Tierney, B. (2018). Data Science. Cambridge, MA: The MIT Press. Available at UM e-library.