This project analyzes tumor growth in mice subjected to various drug regimens. Using data visualization and statistics, it evaluates drug reliability, tumor volume trends, and relationships between weight and treatment outcomes.
Dataset: Merged mouse metadata with study results (1,893 entries).
Scope: 249 unique mice, each monitored over time for tumor growth.
Focus Drugs: Capomulin and Ramicane showed the most consistent tumor volume reductions.
Most mice showed decreasing tumor volumes over time.
A moderate correlation (r = 0.53) was observed between weight and tumor volume.
Capomulin and Ramicane had the lowest variance, suggesting more reliable performance.
Outlier and boxplot analysis confirmed consistent tumor suppression for these regimens.
Python (Pandas, Matplotlib, SciPy)
Data cleaning & merging
Statistical summaries (mean, median, variance, SEM)
Visualizations: bar, pie, box, line, scatter plots
Correlation & regression analysis