Data Analysis Final Report Python Code (Spring 2026)

Data Analysis Final Report Python Code (Spring 2026)

Abstract: Dissolved oxygen (DO) is a critical indicator of water quality and aquatic habitat in rivers, and its variability is strongly influenced by temperature. This study investigates the relationship between air temperature and dissolved oxygen using time‑series data from the Logan River Observatory (LRO) from 2017 to 2023. This analysis focuses on temporal structure through regression diagnostics, smoothing, autocorrelation, cross‑correlation, and hypothesis testing. The results show a strong inverse relationship between air temperature and dissolved oxygen that is more concurrent rather than delayed, with distinct seasonal persistence in both variables. Residual and time‑series analyses further suggest that while a linear model captures the dominant relationship, nonlinear and seasonal structure remains. These findings highlight the importance of temporal context when interpreting the relationship between air temperature and dissolved oxygen in river systems.