How to interpret and use NZCASS results
This section helps you interpret and use the results from the New Zealand Crime and Safety Survey (NZCASS).
What is in scope and out of scope for the NZCASS?
You need to know what the NZCASS covers so you can understand the results and statistics. This webpage tells you:
- who is in scope
- what areas and types of dwellings are in scope
- what offences are in scope.
What is in scope and out of scope for the NZCASS?
How variable are the results?
This webpage covers the sampling error information provided as part of NZCASS reporting. Specifically this page covers:
- what statistical variability is and why we measure it
- how to use sampling error information
- how to know if a difference or change is ‘real’ or not.
Comparability between survey years
Users of the NZCASS need to be able to assess trends by comparing results between years. This webpage provides information on whether changes to different parts of the research were made, and what those changes were.
Comparing NZCASS with Police statistics and ANZSOC classifications
This webpage helps users understand and interpret the statistics produced as part of NZCASS reporting when compared to statistics routinely produced by the NZ Police:
- How do I compare NZCASS statistics and Police statistics?
- Which NZCASS offences can be compared with official Police statistics?
- What adjustments are made?
Comparing NZCASS with Police statistics and ANZSOC classifications
What are the factors of victimisation?
A number of social, demographic and geographic factors are used to understand what types of people are more likely to experience different things associated with crime and victimisation. This page helps users correctly interpret and use the factor information provided as part of NZCASS reporting.
Analysis methods
Different types of analysis have been used to help us better understand different aspects of crime and victimisation. The three advanced methods of modelling used as part of the NZCASS and described in this section are:
- regression
- multiple standardisation
- the Gini coefficient.
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