In this chapter, we will take a real-world univariate and control dataset and run a complete exploratory data analysis workflow on it using the R packages and techniques we covered in Chapter 1, Setting Up Our Data Analysis Environment. After reading and tidying up the data, we will use EDA techniques to map and understand the underlying structure of the data. We will then identify the most important variables in the dataset, test our assumptions to estimate the parameters, and establish the margins of error. We will then explore the dataset graphically using four plots and probability plots. And finally, we will summarize our results in a data report. The code examples will be used from the Bank and Marketing data from UCI.
The following topics will be covered in this chapter:
- Introducing and reading the data
- Cleaning and tidying up the data
- Mapping...