New R Package: Data Science Looks at Discrimination (dsld)

[This article was first published on Mad (Data) Scientist, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

I’m very pleased to announce a new package, dsld, available on CRAN. This is the work of eight talented undergrad students. I provided the concept and some general guidance, but this is their work.

The package is aimed at dealing with discrimination — race, gender, age — in the workplace, education, health care and so on. It consists of analytical, graphical and tabular tools for:

  • detection of discrimination
  • addressing discriminatory predictive models

We hope the package will be useful in a variety of application venues, such as:

  • inspiring motivation in statistics courses
  • discrimination litigation
  • internal HR audits
  • social science research

The usefulness of the package is further enhanced by the availability of a free companion textbook. It uses dsld examples throughout, but its role is to explain the statistical concepts, not to serve as a user manual for the package.

One can acquire a good idea of the nature of the book by reading the example on law school admissions, pp. 34-43.

Needless to say, comments are welcome!

To leave a comment for the author, please follow the link and comment on their blog: Mad (Data) Scientist.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)