Getting Started in the Relationships View
Seek is set up as a workspace with a Display Panel on the left and a Control Panel on the right.
Your selection of regions and data via the Control Panel determines the presentation of data in the Display Panel. To use the Relationships view, you must first select regions and data.*
*If you’ve already selected regions and data in another view, your selections will carry over. You can always change or add to your selections by returning to the Regions and Data modals in the Control Panel.
What You Can Learn from the Relationships View
The Relationships view is one of four different views - or ways of looking at your data and region selections. The others are Table, Map, and Distribution.
The Relationships view is ideal when you are trying to understand the relationship between two variables. The relationship can be positive (if X increases, Y also increases) or negative (if X increases, Y will decrease).
Using the Relationships View
This view includes two visualizations:
Correlation Matrix
The default visualization when you first navigate to this view is the Correlation Matrix, which displays the correlation coefficients, or the strength of the relationship, for all possible pairs of your selected variables.
A correlation coefficient greater than zero indicates a positive relationship, whereas a value less than zero signifies a negative relationship. A value of zero indicates no relationship between the two variables.
Use the legend to determine the strength of the relationship.
Click on any cell in the matrix to bring up the Correlation Details.
Correlation Details
In the scatter plot, the position of each dot on the horizontal and vertical axis indicates values for an individual region. You can hover over a particular dot to view the name of the region it represents and its values for each of the selected indicators.
In the legend below the graph, note the strength and direction of the relationship, the correlation coefficient (or r-value), and the interpretive text.
For further exploration, consider viewing the two variables on a bivariate map. Simply click the green Review as Bivariate Map button to go to the Map view.
