Tableau Strategies

Chapter 2. Quantitative Analysis

This chapter is about crafting visualizations that show distribution, spread, and plenty of nuance. If you’ve ever worked with data, you know it can be a challenge to communicate detailed, complex information in clear and accessible ways. We’ll offer techniques to help you overcome this challenge.

The visualizations in this chapter focus on measures and statistics. Using numeric fields, we’ll show you how different charts can provide different insights through numerical representations of data values. Measures are numeric fields to which we can apply functions, like SUM(). Statistics is, of course, a branch of mathematics; in Tableau, we use its concepts in specialized functions, working with averages, medians, means, standard deviations (SDs), and more. (Don’t worry if you never took statistics in school—we’ll walk you through it!) These functions don’t necessarily produce a summative value, like total sales; instead, they usually describe how the data points are distributed: their highs, their lows, where data points are concentrated, and where the outliers are.

Every dataset has a unique data shape. Most have some common features once you explore them. Some data shapes can be hard to work with, so we’ll also explore techniques to work with those.

In this chapter, we’ll explore the following types of visualizations:

• Histogram

• Dot plot

• Jitterplot

• Ranged dot plot

• Box plot

• Line chart

• Pareto chart

Because we know you’re using these visualizations ...