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" COMPARING ARTIFICIAL NEURAL NET WITH MULTIPLE REGRESSION IN A BIODATA CRITERION VALIDATION STUDY "


Document Type : Latin Dissertation
Language of Document : English
Record Number : 148907
Doc. No : ET20699
Main Entry : James F. Baxter
Title Proper : COMPARING ARTIFICIAL NEURAL NET WITH MULTIPLE REGRESSION IN A BIODATA CRITERION VALIDATION STUDY
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : This research compared Artificial Neural Nets (ANNs) to multiple regression in a Biodatacriterion validation study. Using four constructs derived from 15 Biodata questions, sharedvariance associated with oral interview scores were measured. We proposed: Biodata preselectioninventory will predict Food Server oral interview success (H1); Using sequentialregression, two Education constructs will predict Food Server Oral Interview success (H2); and(step 2) two Experience constructs will account for substantial incremental variance beyond thataccounted for by.
Subject : Electericl tess
: برق
electronic file name : TL43839.pdf
Title and statement of responsibility and : COMPARING ARTIFICIAL NEURAL NET WITH MULTIPLE REGRESSION IN A BIODATA CRITERION VALIDATION STUDY [Thesis]
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TL43839.pdf
TL43839.pdf
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