2.2 Choosing a Data Visualization

There are many, many types of data visualizations. You have gone over some of the most common types in this course, and you will likely encounter others in future stats courses or out in the world. When you want to make a data visualization for a dataset, it can be overwhelming to know where to start! The first thing you need to do is determine the number and type of variables you want to include. We discussed two of the most common data types last lab when looking at data in SPSS:

• Numeric or continuous variables: Measured on a number scale (e.g., age, income, height)
• Categorical variables: Discrete categories, can be ordered (e.g., year of study) or unordered (e.g., undergraduate major)

We will be going over visualizations that include one numeric variable, one categorical variable, and two numeric variables; however, there are many more possible! If you are interested, the resource “From Data to Viz” has suggestions for many types of visualizations.