Data Science Looks At Discrimination 1st Edition Norman Matloff Taha Abdullah Arjun Ashok Shubhada Martha Aditya Mittal Billy Ouattara Jonathan Tran Brandon Zarate by Norman Matloff; Taha Abdullah; Arjun Ashok; Shubhada Martha; Aditya Mittal; Billy Ouattara; Jonathan Tran; Brandon Zarate instant download after payment.

Discrimination is a key social issue in the US and in a number of other countries. There is lots of available data with which one might investigate possible discrimination. But how might such investigations be conducted?
Our dsld package provides both graphical and analytical tools for this purpose. It is widely applicable; here are just a few use cases:
• Quantitative analysis in instruction and research in the social sciences.
• Corporate HR analysis and research.
• Litigation involving discrimination and related issues.
• Concerned citizenry.
This book provides a tutorial regarding applicable methodology, as well as introduction to use of the package.
Two major aspects are covered of the use of data science in discrimination contexts:
Part I: Assessing possible discrimination in observational contexts.
Part II: Ameliorating discrimination in machine learning applications.
The book makes extensive use of the dsld R package, and is best read with access to that software. However, its conceptual content is quite accessible independently of that package.