This report presents a regression analysis of revenue in a departmental store, focusing on the impact of customer quantity, age, gender, and income. The methodology employs regression analysis to identify relationships between revenue and independent variables. Data collected from January 2019, using cluster sampling, is analyzed with variables measured on ratio and nominal scales. The analysis includes ANOVA and regression tables, coefficient significance testing, and multicollinearity checks. The study finds that the regression model is not significant, and the independent variables are not statistically significant predictors of revenue. The report concludes with recommendations for transformations, inclusion of additional variables, and stepwise regression to improve model fit, and emphasizes the need for revised analysis to enhance revenue prediction. The report also includes the necessary plots for checking the assumptions of the regression model.
![[object Object]](/_next/static/media/star-bottom.7253800d.svg)
