Statistical Analysis of Warfare: Identification of Winning Factors with a Focus on Irregular Warfare

Abstract

The purpose of this study was to determine important factors in winning conventional and irregular conflict. The research sought to identify variables and trends for conventional and irregular warfare as a means for predicting battle outcomes. The variables related to conventional and irregular warfare differ. There are limited variables for analysis of irregular conflicts due to the complexity of data collection during these conflicts. Selected variables from both types of conflict were synthesized using a descriptive statistics and decision tree methodology to identify important trends in warfare. The analysis indicated that cavalry, artillery, close air support, air superiority, leadership, and initiative played vital roles in deciding the outcome of conventional battles over time. The exploration of irregular warfare revealed that the population plays a major role in these conflicts. The numbers of participants are higher and the duration is longer in irregular conflict than in conventional warfare. These irregular conflicts primarily occurred in areas of low gross domestic product, low employment-to-population ratio, and government ineffectiveness.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2015
Accession Number
AD1008940

Entities

People

  • Bilal S. Gondal

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Power
  • Asymmetric Warfare
  • Contingency Operations (Military)
  • Conventional Warfare
  • Data Analysis
  • Geography
  • Information Science
  • Military History
  • Military Operations
  • Military Organizations
  • Military Science
  • National Governments
  • National Politics
  • Operations Research
  • Recreation
  • Statistical Analysis
  • Warfare

Readers

  • Military History / Militaries and War Studies
  • Regression Analysis.