Data Health Assurance in Social and Behavioral Sciences Research

Abstract

This illustrative study reincarnates the philosophical assumption of Methodology for science among other assumptions like Epistemology and Ontology in the context of social and behavioral sciences. Based on literature review the study divided the overlapping and perplexing Gaussian Linear Regression Model (GLRM) assumptions into two comprehensive groups. The study modeled straightforward diagnostics for GLRM assumptions violations by using the data collected from 150 postgraduate university students. Finally, the study provides the remedial directions to address possible problems created by GLRM assumptions violations.