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Chatterjee, S., Hadi, A. S. (2006). Regression Analysis by Example. John Wiley & Sons.

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Article

Estimation of Air Quality Index Using Multiple Linear Regression

1Department of Statistics, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India


Applied Ecology and Environmental Sciences. 2022, Vol. 10 No. 12, 717-722
DOI: 10.12691/aees-10-12-3
Copyright © 2022 Science and Education Publishing

Cite this paper:
A. Loganathan, P. Sumithra, V. Deneshkumar. Estimation of Air Quality Index Using Multiple Linear Regression. Applied Ecology and Environmental Sciences. 2022; 10(12):717-722. doi: 10.12691/aees-10-12-3.

Correspondence to: A.  Loganathan, Department of Statistics, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India. Email: loganathan@msuniv.ac.in

Abstract

Air quality index is a numerical measure, which is computed to determine the air quality for various geographical locations. Human activities, industry functioning and climate conditions are some of the significant factors causing variations in the air quality index. Many methods are proposed in the literature and are applied to develop models for investigating the changing behaviour of the air quality index. Among them, regression model is a statistical tool, possessing established properties, recommended frequently for static data. This paper considers estimation of a multiple linear regression model based on the information pertaining to air quality index recorded in a monitoring station located in Chennai, India. Significance of the model to the data is detailed and residual analysis is carried out for testing validity of the fitted model.

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