Logistic Regression and Multiple Linear Regression Applied on Measures Taken by Facebook Users

doi:https://doi.org/10.29350/2411-3514.1280

	Logistic Regression and Multiple Linear Regression Applied on Measures Taken by Facebook Users
Al-Qadisiyah Journal of Pure Science
Volume 29, Issue 2, December 2024, Pages 223-231 PDF (203.95 K)
DOI: https://doi.org/10.29350/2411-3514.1280
Abstract
The research statistically includes checking the suitability of logistic regression or multiple linear regression for modeling the independent variables and the dependent variable, it turns out that logistic regression is more efficient than multiple linear regression as the first one arranges the dependent variables which allows the researcher to conclude that a variable is considered stronger than the other variable. Where applying that has been done to the measures taken by Facebook users, and technically a way to protect the account and dealing with privacy violation and its relationship with electronic hacks, i.e., mail fraud against others for obtaining some classified information. The importance of the research stands out through its attempt to identify the most significant incorporeal determinants by using logistic regression and comparing it with the results via using the multiple linear regression technique, and which one of them is more appropriate that leads to limit the penetrations happening on Facebook users’ accounts. The most important conclusion of the research is the weakness of the multiple linear regression model in the possibility of penetration happening to the accounts while the results of logistic regression clarify the efficiency and suitability of this model for modeling the relationship between the independent variables and the dependent variable.
Keywords
Logistic regression; Linear regression; Facebook

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