A model for and method of predicting high quality Army enlistment contracts.
Faires, Jack E.
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There are many variables that contribute to the explanation of why a person enlists in the Army. To efficiently manage personnel policy in regards to the recruitment process, the impact and significance of these variables needs to be fully understood. Ordinary least squares regression analysis is a powerful and useful tool in helping to explain the interaction of these variables. The understanding of the theories and methods behind this approach is essential. Army analysts apply regression derived results every day in a myriad of situations and operational contexts. Misuse or misunderstanding of these results can lead to inaccurate recommendations to the decision maker. The thesis develops the framework for a parsimonious linear statistical model of quality enlistment contracts for the U.S. Army. There is a need for such a model that can be utilized by USAREC and DCSPER analysts to perform quick response analysis to 'what if' questions. In order to facilitate further model enhancement and use, it is developed in a step-by-step fashion. The author uses a 'walk through' approach and thoroughly discusses the assumptions, procedures and analytical tools that were utilized in the model development. This approach was specifically requested by the Army analysts at USAREC.
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