A Combined Regression and Box-Jenkins Prediction Model for Reenlistment in Selected Navy Ratings.

Abstract

This thesis examines five Navy ratings using two distinct modeling techniques in an effort to predict first term reenlistments. The techniques utilized are Box-Jenkins time series analysis and linear regression. A combined model utilizing both techniques is also developed. The ability of the models ot predict is considered adequate for three of the five ratings and not adequate for two of the ratings. The regression models utilizing 20-24 year old unemployment as the only independent variable yielded surprisingly good predictions, once the time series patterns in the data were modeled. Yeoman, Storekeepers, Operations specialists, electronics technicians and boiler technicians were used in models. Keywords include: Time series; Box-Jenkins methodology; Univariate analysis.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1984
Accession Number
ADA151106

Entities

People

  • K. J. Sherry

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Advanced Electronics
  • Autonomy
  • Biomedical
  • Ground and Sea Platforms
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Age Groups
  • Business Administration
  • Cross Correlation
  • Data Sets
  • Manpower
  • Marine Corps
  • Military Personnel
  • Personnel Management
  • Recruiting
  • Reenlistment
  • Schools
  • Security
  • Standards
  • Statistics
  • Time Series Analysis
  • Unemployment
  • United States

Readers

  • Instructional Design and Training Evaluation.
  • Naval Personnel Management
  • Regression Analysis.

Technology Areas

  • Microelectronics