π 2023-08-25 β Session: Statistical Modeling of Voting Behavior by Gender
π 21:25β21:40
π·οΈ Labels: Voting, Statistics, Beta-Binomial, Ecological Inference, Data Analysis
π Project: Dev
β Priority: MEDIUM
Session Goal
The session aimed to estimate voting behavior by gender using statistical models, specifically the beta-binomial distribution, and to address code execution issues related to this analysis.
Key Activities
- Estimating Voting Behavior: Utilized a beta-binomial distribution to estimate voting behavior of men and women for a political party, detailing the likelihood function and interpretation of estimated proportions across precincts.
- Statistical Approach: Addressed code execution issues and outlined a statistical approach using a binomial distribution to estimate voting proportions by gender.
- Error Correction: Identified and planned to correct an oversight in library imports necessary for calculations.
- Modeling Vote Percentages: Modeled vote percentages using a beta-binomial distribution, providing a step-by-step explanation and pseudo-code for ecological inference based on Kingβs method.
- Ecological Inference Implementation: Implemented Kingβs Ecological Inference using a beta-binomial likelihood function, including defining the likelihood function, objective function, optimization, and result interpretation.
Achievements
- Developed a comprehensive statistical model for estimating voting behavior by gender.
- Identified and planned correction for code execution issues related to library imports.
Pending Tasks
- Import required libraries and rerun the calculations to ensure accuracy and completeness of the model.
- Gather more varied data to achieve nuanced results in voting behavior analysis.