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Doctoral Thesis | Environmental Management | Nigeria | Volume 12 Issue 6, June 2023 | Popularity: 5.4 / 10

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Multivariate Regression Approach to Predict Volume / Quantity of Variables of Plastic-Sand Bricks

Ubak E.M.

Abstract: Regression analysis is a quantitative research method commonly used to investigate relationship between variables. The variables are identified as either dependent or independent, an independent variable is a known variable and has an impact on a dependent variable. In order to predict the value of the dependent variable for factors in which some information concerning the defined variable is available, or estimate the effect of some defined variable on the dependent variable, regression analysis was performed on the research data. Regression allows researchers to predict or explain the variation in one variable based on another variable. Plastic ? sand bricks manufactured from recycling poly ethylene terephthalate (PET) plastic waste was tested for compressive strength and other mechanical characteristics after different plastic: sand ratios experimentation. A desirable brick with appreciable characteristics was obtained which enhanced sound environmental waste management. A viable prediction model for determining the volume/quantity of plastic: sand ratio used was the multivariate regression model, which gives more information in which variables relates and determine the quantity/volume of the data set to produce a brick of any given compression strength. This reduces amount of time, energy and financial resources required during experimental trials of varied plastic: sand ratios to achieve expected compressive strength of the brick. The XLSTAT version 2022 was used for the analysis and the results are presented as Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA).

Keywords: Environment, Plastic ? sand bricks, Poly ethylene terephthalate, Regression analysis

Edition: Volume 12 Issue 6, June 2023

Pages: 1246 - 1253

DOI: https://www.doi.org/10.21275/SR23609012008

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