Assumptions essential for regression models building

Daoud, Jamal I. (2025) Assumptions essential for regression models building. In: 5th International Congress on Scientific Advances (ICONSAD'25), 2025, Bandirma, Turkey.

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Abstract

In regression analysis, most attention must be paid to assumptions about the regression model. One of the objectives of any regression model is to make inferences about the population's model for the same variables. Many assumptions must be tested before model building, while others must be tested after the model is obtained. All tests aim to find the best and most reliable model and make valid and useful inferences about the population parameters. These assumptions are defined, how to detect them, their impact on the model, and how to recover. This paper aims to raise awareness among researchers of the importance of meeting these assumptions, enhance the sense of good understanding of regression analysis and build the best models for the data subject of the study.

Item Type:	Proceeding Paper (Plenary Papers)
Additional Information:	5017/127579
Uncontrolled Keywords:	Regression analysis, Assumption, Linearity, Collinearity, Inference, Heterogeneity
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics Q Science > QA Mathematics > QA300 Analysis
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Science Kulliyyah of Engineering
Depositing User:	Assoc.Prof.Dr Jamal Daoud
Date Deposited:	26 Feb 2026 15:14
Last Modified:	26 Feb 2026 15:29
Queue Number:	2026-02-Q2269
URI:	http://irep.iium.edu.my/id/eprint/127579

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