Summary

This chapter formalized various introductory concepts in statistics and machine learning, including different types of data (categorical, numerical, and ordinal), and the different sub-categories of statistics (descriptive statistics and inferential statistics). During our discussions, we also introduced relevant Python libraries and tools that can help facilitate procedures corresponding to the topics covered. Finally, we briefly touched on a number of other Python libraries, such as statsmodels, PyMC3, and Bokeh, that can serve more complex and advanced purposes in statistics and data analysis.

In the next chapter, we will begin a new part of the book looking at mathematics-heavy topics such as sequences, vectors, complex numbers, and matrices. Specifically, in the next chapter, we will take a deep dive into functions and algebraic equations.