Problem statement
Upload a dataset (CSV with a header row). Choose the dependent variable (demand) and the candidate independent variables. The tool dummy-codes categorical variables, splits the data into training and test sets, selects a model by stepwise regression (VIF screening, then AIC), tests and remedies heteroskedasticity (Breusch–Pagan → Box–Cox), checks normality (Jarque–Bera) and autocorrelation (Durbin–Watson → Cochrane–Orcutt), and finally forecasts the test set and reports accuracy.