Last time we met we took a closer look at bar charts and how we can create bar charts in the different software packages we have access to at the University of Guelph. This time I’d like to change gears a bit and take a look at qualitative data and some of the options that are available to visualize this type of data.
First, qualitative data is a broad term, and the more I work in the field of data & statistics, the more I learn how people define and use the term “qualitative data”. So, I am not going to try to define this term for this session, but rather concentrate on how we can use different types of visualization for this broadly defined type of data.
Resources, there are a large number of resources available to you to help you determine what the best option for your visualization is. I will highlight a couple that I’m currently using. If you are using others, please let me know and I can add them to the list of resources on this site.
Chart Suggestions – Chart suggestions presented by Andrew Abela from Extreme Presentations. A decision chart based on the types of data you are using and the story you want to tell or visualize.
Qualitative Chart Chooser 3.0 by Jennifer Lyons and Stephanie Evergreen. I just came across this wonderful resource. I really like their approach of “What story are you trying to tell?” Let’s work through a couple of examples and discuss your thoughts on this resource.
Books: Data Visualization, A Handbook for Data Driven Design. Andy Kirk (2016).
As you peruse these resources, the one thing that you will notice is that you have to be very comfortable with the type of data you are working with. A quick review:
- Categorical:
- Nominal – groups or levels that do you have any relationship between them or any order
- Examples may include: gender, religion, Yes/No
- Ordinal – groups or levels that have an order to them
- Examples may include: level of education, size, Likert scales
- Nominal – groups or levels that do you have any relationship between them or any order
- Continuous, Scale, Interval, Ratio
- Data that was collected on a scale, interval, or ratio
- Examples may include: age, weight, temperature, weight gain
- Data that was collected on a scale, interval, or ratio
Bring examples of qualitative data to this session and we will look at possible options to visualize the data, the pros, and the cons.
Agricultural Statistics 