4 Case Study: First Look at Data Analysis

In Chapter 2, we introduced the Absenteeism at Work dataset and the business questions it can help answer. In Chapter 3, we learned the basics of R and RStudio. Now it is time to bring the two together. In this chapter, you will load the dataset, inspect its structure, compute basic summary statistics, and create your first visualizations — all using the R skills you just learned.

The goal here is not to build models or draw conclusions. It is simply to look at the data. A careful first look is one of the most important steps in any analysis — it helps you understand what you are working with, spot potential issues, and begin forming questions that deeper analysis can answer.

Chapter Goals

Upon concluding this chapter, readers will be able to:

1. Load a CSV dataset into R from a URL and inspect its dimensions, column names, and data types.
2. Compute and interpret basic summary statistics — including means, medians, and ranges — for key variables in the dataset.
3. Create simple visualizations (histograms, bar charts, and boxplots) to explore the distribution of variables and identify initial patterns.
4. Articulate preliminary observations about the data and connect them to the business questions introduced in Chapter 2.