The article investigates a fully connected linear regression model that combines two types of regression models. The researchers found the best ratio of error variances of independent variables for this model, which improves its predictive accuracy. The study shows that the model performs best when it resembles either a two-factor linear regression or the most accurate single-factor linear regression. This helps in selecting the most informative variables for the regression model.