Crime Trend Prediction Using Regression Models for Salinas, California

Abstract

Salinas, California has been battling an above average crime rate for over 30 years. This is due primarily to two rival gangs in Salinas: the Norte os and the Sure os. The city and the surrounding community have implemented many methods to mitigate the crime level, from community involvement to the inception of a gang task force. As of yet, none of the efforts have had long-lasting effects. In a 2009 thesis, Jason A. Clarke and Tracy L. Onufer postulated that various socio-economic variables are influential on the crime level in Salinas. They characterized "crime" as a summation of homicides, assaults and robberies reported. Their thesis determined that "to lower overall violence levels, officials in Salinas should focus on: reducing the unemployment rate, the number of vacant housing units, and the high school dropout rate; and increasing the high school graduation rate and average daily attendance." A deeper examination of the data could lead not only to assumptions about how to lower crime rates, but also to a means of predicting future crime rates by using various methods of multiple value regression.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2012
Accession Number
ADA563653

Entities

People

  • Jarrod S. Shingleton

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Applied Mathematics
  • California
  • Crime
  • Criminals
  • Data Science
  • Data Sets
  • Employment
  • Families (Human)
  • Information Science
  • Personnel Management
  • Recreation
  • Regression Analysis
  • Statistical Analysis
  • Surveys
  • Task Forces
  • United States

Readers

  • Mathematics or Statistics
  • Political Violence and Terrorism Studies.