Welcome to the “Correlation Analysis” feature of the “Analysis” Hub of LTPP InfoPave! This feature allows you to visualize the relationship among multiple data attributes in the form of a parallel coordinates plot. With just a few clicks through this tour, you’ll be prepared to use the “Correlation Analysis” feature and to perform correlation analyses of your own.

Under the "Find Sections" panel on the left hand side of your screen, there are a number of filters that can assist you in narrowing down your search for LTPP sections. These filters include general information, structure, climate, traffic, and performance filters.

If you point your mouse over each filter, you will see a description that explains how each filter works. For example, you can filter to find sections that are more than 25 years old using the Age filter.

In the “Find Sections” panel bar, you will see different options under filter menu. If you filter your search criteria using “Find Sections,” you can save your filters by clicking on the “Save Filters” option in the “Filter Menu”. When you click on the “Save Filters” menu option, a new window will appear asking you to name your set of filters.

You can then open the saved filters by clicking on the “Open Filters” option in the “Filter Menu.” When you open a saved set of filters, InfoPave will automatically apply your saved filters.

There are twenty attributes currently included in the attribute list. In order to see a correlation in graphical form, you need to select a minimum of two and a maximum of five attributes. After selecting your intended attributes, you will see the correlation in a parallel coordinates plot below the attribute list as well as a table showing all the filtered sections.

The parallel coordinates plot includes a different vertical axis for each selected attribute. Each vertical axis includes the corresponding attribute name and an appropriate scale. The scale for each axis is dynamic, and the scales will change as the section selection changes.

Each line in the plot represents one section with a different color. Each line connects the various data attributes corresponding to that section. The number of lines included in the plot will change as the section selection changes.

If you hover your mouse pointer over a vertical axis, your mouse pointer will change to a plus (+) sign. If you click and drag this plus sign on top of the axis, a slider window will be created. This slider window allows you to subset the data for correlation analysis. You can change the length of the slider window to fit your desired data range. For example, if you want to see the data for test sections that are 10 to 30 years old, create a slider window that ranges from 10 to 30 years on the “Age” attribute axis. If you slide the two limits of the slider window together, the data subset will be cleared.

The correlation table presents the data included in the parallel coordinates plot in tabular form. Each row of the table represents one section. By clicking on the column titles of the correlation table, you can sort the data in ascending or descending order. If you hover your mouse pointer over an individual row in the table, the corresponding line will be highlighted in the parallel coordinates plot.