This is a survey-based research apprenticeship that taught me the rigor of statistical analysis and the importance of embracing non-significant results in the scientific process. As the student researcher, I studied with Professor Shankuan Zhu at Zhejiang University.

Why do patients choose one hospital over another? I sought to decode the complex calculus behind this critical life decision. Under the guidance of a public health expert, I designed and distributed a detailed questionnaire to over 100 patients, focusing on quantifiable factors like commute time, illness severity, and household income.

I transitioned from theory to practice by designing and administering a survey, collecting over 100 responses that provided firsthand exposure to real-world data complexities. This project served as my formal introduction to SPSS, where I mastered data input, cleaning, and key statistical analyses including correlation and regression.

The analysis yielded a crucial insight: none of the hypothesized variables showed statistically significant correlation with hospital choice. While the p-values exceeded conventional thresholds, this null finding revealed an important truth—healthcare decisions are likely driven by complex qualitative factors like trust and personal recommendations, highlighting the limitations of purely quantitative approaches.