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Towards Multiple Regression Analyses for Relationships of Air Quality and Weather

Kevin Kam Fung Yuen
Department of Computer Science and Software Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China
Abstract—Multiple regression is a common data analytic approach to be applied in many areas. The regression objective is to learn regression coefficients, and therefore can be used to evaluate the statistical significant relationships between variables with statistics tests and predict the future values on the basis of the statistical significant relationships. The sample data of air quality and weather in Hong Kong has been analyzed. The pilot study shows factors with statistical significance to pollutant, PM2.5.
 
Index Terms—regression, feature selection, environment analysis, air quality analysis, PM2.5

Cite: Kevin Kam Fung Yuen, "Towards Multiple Regression Analyses for Relationships of Air Quality and Weather," Vol. 8, No. 2, pp. 135-140, May, 2017. doi: 10.12720/jait.8.2.135-140
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