Summary
In this chapter, we looked at different statistical tests, including chi-square and t-tests, as well as point estimates and confidence intervals, in order to ascertain population parameters based on sample data. We were able to find that even with small samples of data, we can make powerful assumptions about the underlying population as a whole.
Using the concepts reviewed in this chapter, data scientists will be able to make inferences about entire datasets based on certain samples of data. In addition, they will be able to use hypothesis tests to gain a better understanding of full datasets, given samples of data.
Statistics is a very wide and expansive subject that cannot truly be covered in a single chapter; however, our understanding of the subject will allow us to carry on and talk more about how we can use statistics and probability in order to communicate our ideas through data science in the next chapter.
In the next chapter, we will discuss different ways...
