In this chapter, we introduced a statistical regression, noted the most common regression approaches, and provided some advice on selecting the correction approach for a particular statistical project. In addition, we mentioned how to identify opportunities for using statistical regression and discussed data summarization, exploring relationships, and testing for significance of the difference.
Finally, we wrapped up with a working example of linear regression modeling for r predicting project profitability.
The next chapter will introduce the developer to the idea of statistical regularization for improving data models in an effort to help comprehend what statistical regularization is and why it is important as well as feel comfortable with various statistical regularization methods.