Implemented Beta-Binomial Model for Voting Analysis

• Day: 2023-08-25
• Time: 21:25 to 21:40
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Voting Analysis, Beta-Binomial, Ecological Inference, Gender Analysis, Statistical Modeling

Description

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.

Evidence

• source_file=2023-08-25.sessions.jsonl, line_number=2, event_count=0, session_id=ca855b157c48ce924235f622a9150c90955f98397dd862d5331be90e4c21eac2
• event_ids: []