A Study of Waste Generation Prediction using Correlation and Multiple Regression Analyses

Abstract

Today, governments, policymakers, and the public are deeply invested in waste generation and environmental preservation. Increased volumes of waste generation continue unabated due mainly to rapid population increase, urban migration, economic enhancements, and modern lifestyles. Two significant factors contributing directly to the higher waste generation volumes are population and gross domestic product (GDP). In Phase 1 of this study, a correlation analysis with a Pearson coefficient of more than 93% (r > 0.93) shows a strong positive linear relationship between the amount of waste generation and population and GDP. Phase 2 provides a multiple regression analysis and the development of a regression model. They indicate that a 1-unit increment in waste generation is caused by 0.06 of the population and 0.119 of GDP while ßo remains constant at 124.449. Therefore, the multiple regression model in this study can be applied by solid waste management authorities in Malaysia to forecast future waste generation volumes accurately. However, further investigation on other significant factors is suggested for future work to develop a holistic model for solid waste management in Malaysia.