As the number of labor and employment class action cases continues to grow, the use of statistical methods will play a more prominent role during litigation. Even though statistical analysis has gained acceptance among the courts in discrimination or compensation equity litigation, persuading non-statisticians about causation poses many challenges.
As legal interpretation of statistical evidence evolves, both plaintiffs and defendants need to be prepared to convincingly communicate that evidence to the court. It is important for legal practitioners to understand the nuances and challenges in proving causation in complex employment litigation and to clearly explain the generally accepted science. Therefore, attorneys and their clients should be aware of current and emerging trends in statistical methods to help them navigate their way in an ever-evolving legal landscape.
In this LIVE Webcast, economists Cary Elliot and Ye Zhang of Resolution Economics LLC will provide an in-depth discussion of the statistical methods used in proving causation in labor and employment class action cases. Speakers will also offer practical tips and best practices aimed at maximizing opportunities while ensuring compliance with the law.
Some of the major topics that will be covered in this course are:
- The difficulty of proving causation in labor and employment litigation
- Overview of statistical analysis of proving causality
- Proving causation in discrimination and compensation equity litigation
- Notable court rulings
- Practical tips and best practices