📅 2023-03-29 — Session: Compiled geospatial and statistical analysis report
🕒 23:20–00:00
🏷️ Labels: Geospatial Analysis, Causal Inference, Data Processing, Project Management, Social Science
📂 Project: Business
⭐ Priority: MEDIUM
Session Goal:
The session aimed to compile and contextualize project accomplishments, focusing on geospatial tasks and data analysis techniques for causal inference in social science research.
Key Activities:
- Described project accomplishments within a collaborative framework.
- Outlined tasks for calculating distances between DHS clusters and road networks.
- Explored data analysis techniques for causal inference, including regression and covariate checks.
- Planned mapping of DHS survey points and visualization of transformed covariates.
- Discussed data processing tasks relevant to social science research.
- Completed a report on analysis and processing tasks related to violent conflict, service delivery, and civic engagement.
Achievements:
- Successfully described project accomplishments and contextualized them within the project’s framework.
- Provided a detailed overview of geospatial analysis tasks and their relevance.
- Compiled data analysis techniques essential for causal inference.
- Planned visualization tasks to identify data patterns and biases.
- Completed a comprehensive report detailing analysis and processing tasks.
Pending Tasks:
- Further exploration of data visualization techniques to enhance understanding of transformed covariates.
- Additional analysis of subgroup data to improve causal inference insights.