Data, Prediction, and Law
LEGALST 123, Spring 2020
Instructor: Jon Marshall
Email: jdmarshall [at] berkeley [dot] edu
Description
Data, Prediction, and Law allows students to explore different data sources that scholars and government officials use to make generalizations and predictions in the realm of law. The course will also introduce critiques of predictive techniques in law. Students will apply the statistical and Python programming skills from Foundations of Data Science to examine a traditional social science dataset, “big data” related to law, and legal text data.
Prerequisites
Students should complete Foundations of Data Science, or complete equivalent preparation in Python and statistics, before enrolling in this course.
Learning objectives
By the end of Data, Prediction, and Law, students will be able to
- use common statistical and computational techniques to analyze and produce visualizations for different types of data (traditional survey data, big data, and text data) related to law; and
- critique the use of data and predictive tools in sociolegal processes, including the identification and punishment of crime.