STATISTICAL ANALYSIS OF TEMPORAL VARIATIONS IN INDOOR RADON DATA USING AN ADAPTED RESPONSE SURFACE METHOD
DOI:
https://doi.org/10.51406/jnset.v14i1.1476Keywords:
ARSM, Indoor radon concentration, Response and Independent Variables, R package and models (i.e. rsm(), lm() and glm()).Abstract
Temporary variations in indoor radon data (IRD), comprising radon concentration (RC), air temperature, relative humidity and barometric pressure were monitored hourly over a period of two months in a bungalow house in Abeokuta, Nigeria. A total of 1510 data was assembled and analyzed statistically using Shapiro-Wilk for normality test, response surface method (RSM) and adapted response surface method (ARSM) to investigate and model the influence of the meteorological parameters on the variations of RC in indoor air. The overall results showed that RC varies widely over time and correlates positively with relative humidity and temperature, but negatively with barometric pressure. Specific results of the two response surface methods were compared and contrasted and the multiple linear regression model of the ARSM was highlighted and established as the appropriate method for analyzing IRD. ARSM was presented in an easily reusable form that can easily be adopted by researchers and data analysts.
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