SIT718: Real World Analytics - Aggregation Functions Assignment

This assignment solution for SIT718 Real World Analytics focuses on applying aggregation functions for data analysis and prediction. The student analyzes a dataset related to energy prediction of domestic appliances, using histograms and scatter plots to visualize relationships between variables like temperature, humidity, and energy consumption. The solution explores various models, including weighted arithmetic mean, power means, and ordered weighted averaging (OWA) functions, to predict energy usage. Error and correlation coefficients are calculated to evaluate the performance of different models. The assignment also involves building a linear regression model and comparing its performance with the OWA model, including a discussion of the significance of variables and model fit. The analysis omits the visibility variable and identifies the best-fit model based on RMSE and error values, concluding with a discussion on the relationships between variables and energy use.