This project investigates the effects of NGN2 viral dose and NT3 treatment on neuronal differentiation efficiency in vitro. Differentiation outcomes were quantified as the proportion of MAP2-positive cells per well, derived from approximately 10,000 cells per condition. To formally assess treatment effects while accounting for the proportional nature of the data and multiple experimental conditions, a binomial generalized linear model (logistic regression) was applied. The analysis identified a clear dose-dependent effect of NGN2, with 5 MOI producing the strongest and most consistent differentiation outcome, and a smaller but significant positive contribution from NT3 treatment. Outlier detection and removal confirmed the robustness of these findings and supported an optimized differentiation protocol.