Real World Analytics: Analysis of Energy Use and Variables

This report presents a comprehensive analysis of real-world data related to appliance energy consumption, utilizing secondary data from energy prediction models. The analysis begins with data visualization, employing histograms and scatter plots to explore relationships between energy use and various environmental variables such as temperature and humidity, both inside and outside a kitchen area, along with visibility. The report then delves into model comparison, evaluating the performance of different analytical techniques, including weighted arithmetic mean, power mean, and ordered weighted averaging (OWA) functions. It identifies the best-fit model based on error and correlation coefficients. The report further develops a linear regression model, providing a detailed comparison with the OWA model and assesses the significance of different variables. Through graphical tools like Q-Q plots, it examines the normality of the data and offers insights into the strengths and weaknesses of each modeling approach, providing a clear understanding of the factors influencing appliance energy consumption.