Summary
In this chapter, we covered many of the basic statistics required for most data scientists – everything from how we obtain/sample data to how to standardize data according to the z-score and applications of the empirical rule. We also reviewed how to take samples for data analysis. In addition, we reviewed various statistical measures, such as the mean and standard deviation, that help describe data.
In the next chapter, we will look at much more advanced applications of statistics. One thing that we will consider is how to use hypothesis tests on data that we can assume to be normal. As we use these tests, we will also quantify our errors and identify the best practices to solve these errors.
