Accession Number:

ADA563653

Title:

Crime Trend Prediction Using Regression Models for Salinas, California

Descriptive Note:

Master's thesis

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s):

Report Date:

2012-06-01

Pagination or Media Count:

89.0

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.

Subject Categories:

  • Economics and Cost Analysis
  • Sociology and Law
  • Numerical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE