# Impact analysis

*Since version 7.18*

Impact analysis evaluates the effect of different subsets of evidence on a target variable and/or state. The target is known as the **Hypothesis**.

Impact analysis can be used to:

- See which individual pieces of evidence change the target the most
- See which individual pieces of evidence, when excluded, change the target the most
- See which subsets of evidence which, when included or excluded, change the target the most.

## Support

Variable type | Hypothesis | Evidence |
---|---|---|

Discrete | Yes | Yes |

Continuous | Yes | Yes |

Hybrid | Yes | Yes |

##### NOTE

We use the term **None** to refer to the case when none of the evidence (being analyzed) is included.
We use the term **All** to refer to the case when all of the evidence (being analyzed) is included.

## Subsets

The subsets to consider are generated by looking at all possible combinations of evidence, subject to the following constraints.

### Max evidence subset size

The number of items of evidence in each subset.

### Subset method

When **Subset method** is set to **Include**, evidence on variables in the subset is included, but not other evidence variables (being analyzed).

When **Subset method** is set to **Exclude**, all evidence is used, except for those in the subset.

## Statistics

For each evidence subset, impact analysis calculates a number of statistics:

### Distance V (from None)

The Kullback-Leibler divergence D(P||Q) from the hypothesis query without evidence (Q) to the current combination (P).

This tells us how different V is between the current subset evidence and no evidence.

### Kullback-Leibler divergence (to All)

The Kullback-Leibler divergence D(P||Q) from the hypothesis query with the current subset of evidence (Q) to all evidence (P).

This tells us how different V is between all evidence and the current subset evidence.

### P(S)

When a discrete hypothesis state is included, this reports the probability of that state given the current evidence subset.

### P(S) - P(None)

When a discrete hypothesis state is included, this reports the difference between the probability of that state given the current evidence subset and no evidence.

### P(All) - P(S)

When a discrete hypothesis state is included, this reports the difference between the probability of that state given *All* the evidence and the current evidence subset.

### P(S) / P(None)

When a discrete hypothesis state is included, this reports the ratio between the probability of that state given the current evidence subset and no evidence.

##### NOTE

This is also known as the **Normalized Likelihood** in impact analysis.

### P(All) / P(S)

When a discrete hypothesis state is included, this reports the ratio between the probability of that state given *All* the evidence and the current evidence subset.