Today I just discussed and started working on a report for Project 1 with my teammates. We just found 5 issues to evaluate in the report which are affecting %diabetes in addition to %obesity and %inactivity. And apart from the report, I’ve started working on the cross-validation part to enhance model accuracy.
I delved into a comprehensive exploration of the Breusch-Pagan test, learning its role in assessing heteroscedasticity within regression models. Heteroscedasticity denotes a scenario where the variance of regression model error terms varies unevenly across different levels of independent variables, thereby challenging a fundamental assumption of linear regression. The Breusch-Pagan test scrutinizes whether a noteworthy correlation exists between the squared residuals of a regression model and its independent variables. When the test reveals a significant relationship, it signals the presence of heteroscedasticity, necessitating adjustments or transformations to rectify this issue in our regression analysis.