Mini-Project 2: Visualizing your data

Reminder of the class project

The mini-projects and final project are intended to give you the chance to practice the workflows and techniques that we cover in class in the context of a complete analysis. Because each of you are in different stages of collecting your own data and because confronting datasets that aren’t yours can help clarify important concepts and design elements, I’m asking you to develop an analysis of data that isn’t yours.

The goal here is to have you gain some experience finding spatial data, thinking about an interesting question where the geographic location is (at least partially) important in determining how we might think about the process that gives rise to the data, and developing an analysis and suite of visualizations that help you (and others) better understand that process.

Mini-project 2

Now that you’ve built a spatial database, it’s time to start making some sense of it. One way to do that is by visualizing the data, either using maps or other types of plots. That’s the goal of this assignment. Given your research question and ‘hypotheses’ (I’m using this term loosely because you are [hopefully] using data that you’re not terribly familiar with), this project asks you to:

• Develop two static maps that display the relationship between your dependent variables and one or more of your predictor variables

• Develop one interactive map that allows you to explore potential correlations/relations between your predictor variables

• Develop two additional non-spatial visualizations that attempt to characterize the same relations without using a map

• Submit a knittable Rmarkdown document that describes your research question and what you hope to learn from the visualizations you develop. Your document should also include reflections on the effectiveness of each visualization. How does mapping help or confuse relationships? How do interactive maps facilitate different kinds of explorations compared with static maps? How does what you’ve learned about these different visualizations inform how you might approach planning an analysis and presenting the results? As always, your document should also include well-annotated code that allows me to reproduce the figures.