Preconceived assumptions and biases—whether conscious or not—can creep into all aspects of data analysis, from coding data to interpreting findings. In this two-part blog post, Network member Lois Joy examines the need for applying an equity lens during quantitative data analysis (Part 1) and describes approaches that support equity and reduce bias (Part 2).

The ideas and suggestions presented correspond with Stage 4 in the Equity Framework for CTE Research. Developed by the CTE Research Network’s Equity Working Group, this framework illustrates how researchers can infuse an equity approach into social science research from start to finish.

This two-part blog post represents the fourth and fifth posts in a series featured on the Sage Methodspace.

• Blog Post 1: Equity Framework for Research Design and Practice
• Blog Post 2: Using an Equity Lens to Design Your Research
• Blog Post 3: Using an Equity Lens in Measurement and Data Collection
• Blog Post 4: Part One: The Need for Equity Approaches in Quantitative Analysis
• Blog Post 5: Part Two: Equity Approaches in Quantitative Analysis
• Blog Post 6: Disseminating Research with an Equity-Focused Lens