Background. In data analysis issues, stepwise multiple linear regression is seen to be a very helpful computational method. Multiple linear regression (MLR), logistic regression, ordinal regression and multinominal regression are all examples of regressions. Multiple linear regressions are a type of linear regression analysis that is used to examine the relationship between a single response variable (the dependent variable) and two or more controlled variables (the independent variables).

Objective. This research aims to comprehensively investigate and address the multifaceted issue of water pollution.

Methods and materials. Data were obtained using an online questionnaire form, where the questionnaire was sent to the target group. There were four general steps to build questionnaire model in MLR. The general steps were supersaturated designs, checking assumptions, choosing appropriate multiple variables analysis, and interpreting the output. Each model was analyzed separately using the chosen analysis methods using a program Statistical Package for the Social Sciences 20.

Results. The stepwise regression method for all applications reveals that five controlled variables were chosen using SPSS 20:  w₂, w₅, w₉, and w₁₃.

Conclusion. w₂  (increase in population), w₅ (inorganic materials such as (copper, mercury, etc.), w₉  (rainwater), w₁₁ (waste chemicals) and  w₁₃ (waste of living organisms) are the actual causes of water pollution.

water pollution, multiple linear regressions, supersaturated designs, data analysis, Saudi Arabia.

Received: June 11, 2024; Revised: July 19, 2024; Accepted: July 31, 2024; Published: October 3, 2024

How to cite this article: Itidal Ali Albalawi, Mohammad A. Abdulhakeem and Waleed B. ALShammari, Application of stepwise multiple regression to supersaturated designs data of water pollution in Saudi Arabia, JP Journal of Biostatistics 24(3) (2024), 487-515. https://doi.org/10.17654/0973514324027

This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License

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