Data conclusions

With a strong sense of the data at hand, given by wrangling, summarizing, and visualizing, modeling the data can often provide extended insight.

13  Functions + iteration provides details on working with functions and mapping them across multiple iterations. Functions provide a structure for iterated operations on the data, and they make code less error prone, more efficient, and more readable.

Machine learning techniques are not covered here but do fall into the category of data conclusions; additionally, they are an important part of data science! In 14  Permutation tests we cover permutation tests which allow for inferential claims about a population from which the data came.