SOL Prep

Data Bias

Virginia SOL DS.4

Identify biases in data collection and understand implications and privacy issues.

Study DS.4 with SOL PrepBack to Data Science

What students need to be able to do

  • Identify data biases in the collection process (e.g., confirmation, selection, outliers, overfitting/underfitting, confounding) and describe mitigation strategies.
  • Provide examples of sampling biases and their potential effects.
  • Identify and describe data biases as both a producer and consumer of data.
  • Describe how data collection should be focused, relevant, and limited to the scope of the data project plan.
  • Describe privacy considerations in data collection as both a consumer and producer.