📅 2023-08-25 — Session: Implemented Beta-Binomial Model for Voting Analysis
🕒 21:25–21:40
🏷️ Labels: Voting Analysis, Beta-Binomial, Ecological Inference, Gender Analysis, Statistical Modeling
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal: The session aimed to estimate voting behavior by gender using statistical models, specifically focusing on the beta-binomial distribution and ecological inference.
Key Activities:
- Explored the process of estimating voting behavior using a beta-binomial distribution, including the likelihood function and interpretation of estimated proportions for different precincts.
- Addressed a code execution issue related to statistical modeling, focusing on estimating voting proportions by gender using a binomial distribution.
- Corrected an oversight in library imports, ensuring all necessary libraries were included for calculations.
- Discussed the computed estimates of voting behavior for men and women, highlighting the need for more varied data for nuanced results.
- Outlined a method for modeling vote percentages using a beta-binomial distribution, providing a step-by-step explanation and pseudo-code for ecological inference based on King’s method.
- Implemented King’s Ecological Inference on voting data using a Beta-Binomial likelihood function, defining the likelihood function, objective function, optimization, and result interpretation.
Achievements:
- Successfully implemented a beta-binomial model for analyzing voting behavior by gender.
- Corrected library import issues, ensuring smooth code execution.
Pending Tasks:
- Gather more varied data to improve the accuracy and nuance of the voting behavior estimates.