# Indexed reports

### From Wiki

An indexed report is intended to put data into context, by indicating whether individual items of information are over or under represented compared to the norm.

MAST indexed reports display not only a measure, but also an index bar for each data point in chart view.

## Contents |

## Mosaic Profiles with indexing

In the Initial Version of MAST, the only type of indexing which has been implemented compares the backgrounds of people involved in crashes to the corresponding population base.

Reports can only show indexing under the following circumstances:

- The report is based on either Vehicles or Casualties
- The only dimension used as a category is either Driver Mosaic or Casualty Mosaic
- The report contains no series
- The report filters include either Driver Home or Casualty Home
*NOTE:*This required 'Home' filter only has to be present - it does not necessarily have to be applied (so it could be set to**All**)

## Understanding Indices

Indices are expressed with a base value of 100: that is, an index value of 100 indicates that the corresponding data point is exactly representative of the underlying population, neither larger or smaller than would be expected. values over 100 indicate that a data point is over represented, while values under 100 indicate relative under-representation.

When interpreting index values, the following techniques should always be used:

**Filter out Z in the Mosaic category**because Mosaic Group Z represents postcodes which were missing in STATS19 returns, and they distort the index calculation.**Look carefully at the chart value axis**because sample size makes a big difference to the significance of indices - an index of 115 on a sample of 1,000 would probably be significant, but an index of 180 on a sample of 20 would probably be unreliable.**If you apply a Home filter, avoid multiple selections and always clear the NK and Unknown boxes**because basing the the index calculation on eccentric collections of areas and missing postcodes would probably give meaningful results.**Don't use a Crash Location filter unless you have also applied a matching Home filter**because the geographic extent of crashes should be broadly consistent with the profile of the base population - if it was not, the index calculation would probably be distorted.

## Index calculation algorithm

The method of calculation is as follows:

( {Value of data point} / {Value of all data points} ) / ( {Population corresponding to data point} / {Total population} ) * 100

## Index calculation example

Group H drivers constitute 223 out of a total sample of 1,328 (16.8%)

Group H residents constitute 11,278 out of a total local population of 76,589 (14.7%)

The index value for the H data point is 114 ( 16.8% / 14.7% * 100 )

## Future expansion of indexing functionality

It is intended that future versions of MAST will apply the concept of indexing much more widely. More rigorous features to ensure statistical significance are also being planned.