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Spring 2020
6372 Analytic Methods for Lawyers - CHANDLER- 22535

Professor(s): Seth Chandler (FACULTY)

Credits: 3

Course Areas: Business and Commercial Law 
Law And Society/ Interdisciplinary

Time: 1:00p-2:30p  TTH  Location: 3  BLB

Course Outline: This course will expose students to a diverse set of computational skills that should prove useful in understanding law, expert testimony, and the latest in legal technology. Areas addressed in this survey will include (1) databases, including relational operators, normalizations and data cleansing; (2) statistics and statistical testing, including the meaning of p-values, statistical power, various forms of regression, and how to depose a statistical expert; (3) basic finance, including exposure to actuarial finance; (4) useful visualizations of data, including production of demonstrative evidence for courts; (5) a very significant study of machine learning, including supervised, unsupervised and reinforcement learning and methods such as decision trees, neural networks, random forests, and Monte Carlo tree search; (6) computational linguistics, which is basically the application of statistics and machine learning to textual data; and (7) analysis of networks, including precedent networks and affiliation networks.

Unlike in years past, students will not be required to learn to write computer programs. In his own exposition, however, the instructor will make extensive use of Mathematica (the Wolfram Language), but will also expose students to R, Python, Julia and the Jupyter programming notebook. The student will thus gain some very basic "reading knowledge" of programming.

No programming background is assumed for this course nor is any advanced mathematical background required. It will help somewhat if students have been exposed to calculus and to linear algebra (matrices), even if they no longer remember how to do an integral or perform matrix operations. Students who have always hated or done poorly at math should probably avoid this course.

Students will be evaluated on the basis of (1) a final exam and (2) a 10-page paper in which they demonstrate how some form of computation studied in the course could illuminate a legal problem or explore a data set relevant to law.

Course Syllabus: Syllabus

Course Notes:   Quota = 15.

Prerequisites:  

First Day Assignments:

Final Exam Schedule: 04/30 1-4pm      

This course will have:
Exam:
Paper:

Satisfies Skills Course Requirement: No
Satisfies Senior Upper Level Writing Requirement: No

Experiential Course Type: No

Bar Course: No

DistanceEd ABA 306:

Pass-Fail Student Election:

Course Materials (12/3/2019 11:44:10 AM)

No book required for this course