Residential energy consumption constitutes a significant portion of the overall energy consumption. There are significant amount of studies that target to reduce this consumption, and these studies mainly create mathematical models to represent and regenerate the energy consumption of individual houses. Most of these models assume that the residential energy consumption can be classified and then predicted based on the household size. As a result, most of the previous studies suggest that the household size can be treated as an independent variable which can be used to predict energy consumption. In this work, we test this hypothesis on a large residential energy consumption dataset that also includes demographic information. Our results show that other variables such as income, geographic location, house type, and personal preferences strongly impact energy consumption and decrease the importance of the household size because the household size can explain only 26.55% of the electricity consumption variation across the houses.

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