Bias.7z

Use visualizations like histograms or heatmaps to show where the "bias" exists in the data.

Explain how you tested for bias (e.g., checking for disproportionate outcomes across demographic groups). Bias.7z

A high-level overview of what the archive contains (e.g., "The archive contains memory dumps and network logs related to an unauthorized access event"). Use visualizations like histograms or heatmaps to show

If the file contains datasets (e.g., CSV or JSON files) used to study algorithmic fairness, your paper should focus on the statistical implications: Bias.7z

In some academic contexts, "Bias" refers specifically to errors in trade classification models. If your paper is about market microstructure:

Suggest ways to "de-bias" the model, such as re-weighting the data or using a GMM estimator for improved estimation . Option 3: Financial Trade Classification