Lesson 7 Lab

Lesson 7 Lab 

Multivariate Symbolization 

In Lab 6, we explored representing discrete and abrupt data using proportional symbols. Specifically, you worked with proportional and graduated sybmbols. You also explored mapping qualitative data using the chorochromatic symbolization. In Lab 7, you will continue to apply design and symbolization ideas. In most cases, your maps have focused on one representing a single data variable (e.g., % of people with health insurance), or layered different kinds of data (e.g., race routes layered over terrain). Univariate data is one of the more common data that is mapped. However, symbolization methods exist that allow more than one variable to be mapped. This Lab, we introduce multivariate mapping—maps that visualize more than one data attribute at once. 

Following our general discussion of multivariate maps, we introduce a special type of data—uncertainty. When mapping predicted flood zones, for example, we might want the reader to understand not only the predicted flood values across the map, but their associated uncertainty—how certain those values are to reflect reality across different locations. As uncertainty plays a pivotal role in decision-making, we close out our discussion of uncertainty visualization with a short summary of its influence on decision-making with maps. In Lab 7, we explore both multivariate data and uncertainty visualization techniques while creating maps using the reported margin of error reported in census data.

As with Lab 6, Lab 7 will continue using Tableau to create the maps. However, the emphasis on using Tableau for Lab 7 will extend beyond multivariate symbolization to creating an interactive dashboard where maps and graphics will be linked together alllowing relations in the data to be seen.  

This lab, which you will submit at the end of Lesson 7, will be reviewed/critiqued by one of your classmates in Lesson 8 (critique #4). 

Lab Objectives 

• Create a single dashboard in Tableau which includes the following  main elements:
  • a multivariate map using proportional symbols (separate legends for each variable)
  • a chart showing the variable of interest
  • a chart showing the margin of error values
• Create a single multivariate map using census data (either the same data from Lab 6 or new data) 
• Visualize the census data and unercertainty data on a single map using appropriate combination of visual variables and colors to create a multivariate map
• Create two charts (e.g., scatterplots) that illustrate the census data values and the uncertainty (e.g., margin of error)
• Integrate the multivariate map and two charts together on a single dashboard through linking so that relations highlighted on one object (e.g., the map) are also highlighted on another (e.g., both charts) creating a dynamic environment
• Implement an effective unified design practice (color choices, balancing negative space, etc.)

Overall Lab Requirements 

For Lab 7, you will create a single dashboard of a unified design in Tableau. The specific requirements for each dashboard element are listed below. 

Lab Requirements 

Multivariate Map: Variable of Interest and Uncertainty Data

• Choose a variable of interest to map from the provided American Community Survey (ACS) data to create a single multivariate map
• You can use the same data from Lab 6 (or choose a different dataset), but the data must also include a measure of uncertainty (for census data, this uncertaintly can be considered the margin of error values included as a separate column with the census data) 
• The chosen data will be mapped using a bivariate symbolization (e.g., symbols and color values) 
• Use appropriate visual variables to encode your data using a bivariate symbolization

Chart One: Census Data (choose your own variable) 

• Select an appropriate chart representation method (e.g., scatterplot, barchart, etc.) to represent the pattern between the census data value and each county
• This chart must be linked to the bivariate map and other chart so that and data relations highlighted on one element are also highlighted on another creating a linked environment 
• The chart title must correspond to the data appearing on the chart
• Consideration must also be given to the design of the chart (e.g., unique color choice for the symbols, axes titles, data order along both axes, etc.)

Chart Two: Census Data (use the variable's margin of error) 

• Select an appropriate chart representation method (e.g., scatterplot, barchart, etc.) to represent the pattern between the census data and the margin of error by county (note, you can use the same chart type as with Chart One or choose a different chart type)
• This chart must be linked to the bivariate map and other chart so that and data relations highlighted on one element are also highlighted on another creating a linked environment 
• The chart title must correspond to the data appearing on the chart
• Consideration must also be given to the design of the chart (e.g., unique color choice for the symbols, axes titles, data order along both axes, etc.)

Tableau Dashboard 

• Appropriately arrange and size each object in the available dashboard space (e.g., consider the distribution of negative space)
• Ensuring that each object is linked to the other objects on the dashboard
• All objects need to be clearly visible and readable (e.g., be mindful of text size)
• Create an overall descriptive title and individual object titles
• Use consistent design appearance and feel throughout the story

Lab Instructions 

The data for this lab will be self-selected from the US Census Bureau’s data explorer website. Details on how to access this site, how to search for data, and format the data for download was presented in the Lesson 6 Lab Visual Guide. 

Grading Criteria 

A rubric is posted for your review. 

Submission Instructions 

Ready to Begin? 

Detaield instructions on creating these objects are available in the Lesson 7 Lab Visual Guide.