Abstract
Statistical analyses are important for real-world validation of theoretical model predictions. In this article, a statistical analysis of real data shows empirically how thermal resistance, thermal mass, building design, season and external air temperature collectively affect indoor air temperature. A simple, four-point, diurnal, temperature-by-time profile is used to summarise daily thermal performance and is used as the response variable for the analysis of performance. The findings from the statistical analysis imply that, at least for moderate climates, the best performing construction/design will be one in which insulation and thermal mass arrangements can be dynamically altered to suit weather and season.
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