What is the Data Relationships Tool?

The Data Relationships tool is used for investigating the relationships between different column pairs. The tool always works on the currently filtered data. The Linear regression and the Spearman R options allow you to compare numerical columns, the Anova option will help you determine how well a category column categorizes values in a (numerical) value column, the Kruskal-Wallis option is used to compare sortable columns to categorical columns, and the Chi-square option helps you to compare categorical columns.

For each combination of columns, the tool calculates a p-value, representing the degree to which the first column predicts values in the second column. A low p-value indicates a probable strong connection between two columns.

The resulting table displays the p-value for each combination of Y and X columns. The table is sorted by p-value. Clicking on a column heading will sort the rows according to that column.


Consider the following data table, which lists a few attributes of a group of people:


Eye color, Gender, Height (m), Weight (kg), Age

blue, female, 1.65, 62.7, 29

blue, female, 1.50, 57.0, 31

blue, female, 1.69, 64.2, 18

blue, male, 1.58, 63.2, 31

green, male, 1.76, 70.4, 44

green, male, 1.82, 72.8, 26

green, male, 1.92, 76.8, 33

green, female, 1.54, 61.6, 39

green, female, 1.76, 70.4, 22

brown, female, 1.67, 66.8, 34

brown, female, 1.47, 58.8, 41

brown, male, 1.69, 71.0, 23

brown, male, 1.78, 74.8, 35

brown, male, 1.83, 76.9, 20

brown, female, 1.62, 87, 62

blue, male, 1.87, 86.5, 23

brown, male, 1.76, 92, 65

brown, male, 1.62, 59, 13

green, female, 1.70, 59, 32

(To test the example, copy all of the above text and paste it in TIBCO Spotfire.)

  1. Select Tools > Data Relationships....

    Response: The Data Relationships dialog is displayed.

  2. Select Linear Regression (numerical vs numerical) as the comparison method.

  3. Send all Available Y-columns to the Selected Y-columns list by clicking on them in the list and then click on Add >.

  4. Send all Available X-columns to the Selected X-columns list by clicking on them in the list and then click on Add >.

  5. Click OK.

    Response: A new data relationships table is created, together with a scatter plot based on the marked row in the table.


The scatter plot shows the Y and X column from the currently marked row in the data relationships table. Since Height vs. Weight got the lowest p-value of all columns investigated, this column pair is listed first in the data relationships table, and is marked by default. Not surprisingly, it appears as if there is a correlation between the Height and Weight of the test persons.

By clicking on a different row in the data relationships table, the scatter plot changes to display the new column pair:


The p-value for Age vs. Height is quite high and according to the scatter plot, there does not seem to be any significant correlation between those two columns in the current data.

See also:

How to Use Data Relationships

Details on Data Relationships