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Author: United States. Adjutant-General's Office. Personnel Research Branch
Publisher:
ISBN:
Category : Prediction of scholastic success
Languages : en
Pages : 26
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Book Description
Author: United States. Adjutant-General's Office. Personnel Research Branch
Publisher:
ISBN:
Category : Prediction of scholastic success
Languages : en
Pages : 26
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category : Prediction of scholastic success
Languages : en
Pages : 13
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Book Description
Author: United States. Adjutant-General's Office. Personnel Research Branch
Publisher:
ISBN:
Category : Prediction of scholastic success
Languages : en
Pages : 20
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Book Description
Author: ADJUTANT GENERAL'S OFFICE (ARMY) WASHINGTON DC.
Publisher:
ISBN:
Category :
Languages : en
Pages : 14
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Book Description
Author: ADJUTANT GENERAL'S OFFICE (ARMY) WASHINGTON DC.
Publisher:
ISBN:
Category :
Languages : en
Pages : 9
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Book Description
Author: United States. Adjutant-General's Office. Personnel Research Branch
Publisher:
ISBN:
Category : Psychology
Languages : en
Pages : 20
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Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 632
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Book Description
Author: Trevor J. Ritland
Publisher:
ISBN:
Category : Operations research
Languages : en
Pages : 57
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Book Description
This thesis is a follow-on study to the Master of Business Administration (MBA) project, Grade Point Average as a Predictor of Success at Explosive Ordnance Disposal Training, completed in December 2009 by Lieutenant Sarah Turse and this author. The purpose of this thesis is to analyze, develop and provide a more accurate student graduation prediction model than the current model in place at Naval School Explosive Ordnance Disposal (NAVSCOLEOD). The school's current model was produced five year ago using ordinary linear regression. This outdated model was compared to the new model generated in this study using statistical techniques such as receiver operating characteristic (ROC) curves and the Hosmer-Lemeshow test. Our analysis finds that the student's branch of service, GPA, and the division in which the student failed each significantly impact predicting a student's future. We also find that the interaction between GPA and division also significantly impacts the prediction. Finally, we conclude that using a logistic regression instead a linear regression captures the binary output (graduated or did not graduate) better. Our improved model increases the prediction probability by roughly 2 percent using student data from 2004 to 2008.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 496
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Author: L. Harold Sharp
Publisher:
ISBN:
Category : Electric machinery
Languages : en
Pages : 30
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Book Description
"This study was one of a series to evaluate the effectiveness of the Army Classification Battery, particularly the Electronic Aptitude Area composite, in predicting performance in electronics and electrical equipment repair jobs"--Preliminary page.
