This chapter covers
- Tips for putting your statistics (chapter 7) and software (chapters 8–9) into action
- When to modify the plan (formulated as in chapter 6)
- Understanding the significance of results and how it relates to practical usefulness
Figure 10.1 shows where we are in the data science process: executing the build plan for the product. In the last three chapters, I covered statistics, statistical software, and some supplemental software. Those chapters provide a survey of technical options available to data scientists in the course of their projects, but they don’t continue along the data science process from the previous chapters. Because of this, in this chapter I bring you back to that process by illustrating how you can go from the formulation of a plan (chapter 6) to applying statistics (chapter 7) and software (chapters 8 and 9) in order to achieve good results. I point out some helpful strategies as well as some potential pitfalls, and I discuss what it might mean to have good results. Finally, I give a thorough case study from a project early in my career, with a focus on applying ideas from the current chapter as well as the previous few.
