Research

In UX design, data-driven insights are crucial for understanding user behavior and optimizing experiences. I use quantitative analysis tools to uncover patterns, validate design decisions, and enhance product strategy. By applying methods like ANOVA, Chi-Square tests, and regression analysis, I can translate user data into actionable insights, ensuring that design choices are not just intuitive but also measurable and evidence-based.

Using Statistical Analysis to Understand User Behavior and Market Trends

This research note introduces three core statistical methods—ANOVA (Analysis of Variance), Chi-Square Test, and Multiple Regression—and how they help UX researchers and product teams make data-driven decisions.