The goal of representation testing is to assess whether a dataset accurately represents a specific population or if biases within it could adversely affect the results of any analysis.

How it works:

  • From the dataset, it extracts the original sentence.
  • Subsequently, it employs a classifier or dictionary is used to determine representation proportion and representation count based on the applied test. This includes calculating gender names, ethnicity names, religion names, or country names according to the applied test criteria. Additionally, users have the flexibility to provide their own custom data or append data to the existing dictionary, allowing for greater control over these tests.