Applying Factor Analysis to Population Surveys in Afghanistan to Facilitate Improved Decision Making

Open Access
Article
Conference Proceedings
Authors: Capt. Joseph K. Maddux

Abstract: As the U.S. Military’s involvement in Afghanistan has changed from a traditional kinetic fight to counter-insurgency to nation building, so too has our need to understand the population which we seek to assist. Multiple agencies have taken on the task of surveying Afghans at the national, provincial and district levels. Conducting these surveys carries great risk due to the presence of Taliban fighters and terrorist safe havens strewn throughout the country. While conducting the surveys has its share of obstacles, properly interpreting the results carry its own unique set of challenges. We use three surveys that have been mainstays as sources of information for the U.S. Military and other nations to understand popular perceptions. Using Factor Analysis on these three surveys collected over the last 3-5 years allows us to analyze all questions and responses in the surveys by identifying the most relevant data analytically vice a subjective analyst or commander deciding what is most important. We do so by using a methodology that establishes quality, analytically derived indicators (groups of survey questions) by using these three survey instruments collected throughout Afghanistan. We generate indicators from survey data using Factor Analysis then assess them by using nonparametric statistics techniques to detect spatial and temporal changes throughout the country. The final result is a full analytics suite that provides perspective to an analyst regarding indicator change across the country over time. Further, we improve the commander’s ability to allocate scarce resources to particular districts and provinces which need the most attention.

Keywords: Factor Analysis, Survey, Non-Parametric Statistics, Mann-Whitney, Military, Afghanistan, Spatial and Temporal change, Spreadsheet, Hypothesis Testing, Analytics

DOI: 10.54941/ahfe100199

Cite this paper:

Downloads
1286
Visits
2118
Download