# Interpret the organic tree

The Organic Tree provides an overview of the statistical relationships between nodes. In later releases there will be flexibility about how the tree is displayed.

At present the following applies:

- The width of a branch is proportional to the number of people in that node.
- The angle of a branch indicates how significant the difference in *Analysis %* within the branch is compared to its parent.

  A branch almost in line with its parent, does not differ that significantly in *Analysis %*

  A branch sticking out at a large angle, shows a significant difference in *Analysis %*
- The colours are as explained in the section [What do all the colours mean?](<https://help.apteco.com/en/faststats/modelling/decision-tree/using-the-output/colours/index.md>):

  Grey - node *Analysis %* similar to that of the root node

  Red - node *Analysis %* greater than that of the root node

  Blue - node *Analysis %* less than that of the root node

## Some examples of organic trees

### Significant but low gain

In the above example most of the splits are highly significant (large angles), but are only resulting in small changes to the *Analysis %* (colours are muted or grey). This is because the root node has a very high *Analysis %*, of 82%. This has two consequences:

- Changes in *Analysis %* are never very large.

  The best node, with an *Analysis %* of 96%, still only has a gain of 1.17 and so is only lightly shaded. Similarly, the worst node, with an *Analysis %* of 55%, has a gain of 0.67, which is still close to 1.0 and so very lightly coloured.
- Changes in *Analysis %* are, however, very significant.

  Since changes in *Analysis %* are based on large samples they are typically very significant. Node 1 (shaded grey) represents a change in *Analysis %* from 82% to 90%, which has a *Z-Score* of 142.

### High gain but not significant

In the above example most of the splits represent large changes to the *Analysis %* (bold colours), which are not very significant (small angles). This is because the root node has a very low *Analysis %*, of 0.0005% (10 out of 2 million!). This has two consequences:

- Changes in *Analysis %* are typically very large.

  The best node, with an *Analysis %* of 50% (2 people out of 4), has a gain of almost 100,000, and so is very intense red. Similarly, the worst nodes, have an *Analysis %* of 0%, have a gain of 0, and so are very intense blue.
- Changes in *Analysis %* are, however, not very significant.

  Since changes in *Analysis %* are based on small counts, and are changes to what is initially a very low percentage, they are typically of very low significance. Node 1 (shaded light red) represents a change in *Analysis %* from 0.0005% to 0.001%, has a *Z-Score* of 2.48.

  In statistical terms this is officially classed as significant, but that is mainly due to the very large samples available in marketing data. However, dealing with counts of 10 in a few million, although statistically classed as significant, is not likely to have business significance!