Once we pass our model evaluation and decide to select the estimated model as our final model, we need to interpret the results to the company executives and also their technicians.
In the following, we discuss some commonly used ways of interpreting our results, one using tables and another using graphs, with our focus on impact assessment.
Some users may prefer to interpret our results in terms of ROIs, for which the cost and benefit data is needed. Once we have the cost and benefit data, our results here can be easily expanded to cover the ROI issues. Also, some optimization may need to be applied for real decision making.
As discussed in section, Spark for a holistic view, the main purpose of this project is to gain a holistic view of sales team success. For example, the company wishes to understand the impact of marketing on sales success in comparison to training and other factors.
As we have our linear regression model estimated, one easy way of comparing...