On your data

CorrExplore maps the "space" formed by relationships among any set of variables. Whether or not your data has an interesting implicit "space", CorrExplore can give an overview of data relationships and reveal relational differences across segments. Example uses:

Political space Brand positioning Non-spatial data

Key features:

Segmentation: Divide and compare maps using any variable

Use any variable to segment into:

One map for each unique value of the variable
A median split: one map for high values, one for low
Custom segments: choose your own ranges of values

Animated transitions between segments make comparison easy
Can segment by time to show change

Animated/interactive: better data communication, not data reduction

Variables move because they are pulled by their positive correlations and pushed by their negative ones. Technically, this uses a variant of multidimensional scaling designed for correlation networks.
An Animated display conveys more information without clutter:

See the model running, instead of just a final resting state
Hover over a variable to view its relationships
Per-variable stress coloring, not just an overall model fit

Interactive to rapidly explore possibilities

Drag and drop variables to explore alternative resting states
Hide variables to examine the internal structure of a cluster
Reverse-code variables with a right click
Double click to fix a variable in place

Free viewer: Share animated, interactive views with anyone

Only registered users can import their own data
Registered users can also create view files
Views are better than snapshots, with all of the animation & interaction benefits listed above.
Built-in demo data lets you try all features before registering.

Visually explore correlation networks