Introduction
A scatterplot is one of the easiest and more effective ways of investigating your datasets. It is a great way of ‘eyeballing’ your data to see how the variables are distributed and relate to each other. A scatterplot is not a rigourous statistical analysis, but is a very useful ‘first pass’ of data, to visualise obvious or not so obvious correlations and relationships.
The AURIN portal has two ways of creating a scatterplot from your data – the interactive scatterplot described here allows you to interact with each of the data-points and where they fit on your map, while the scatterplot described in the Chart Tools is more “bare-bones”, although it allows you easy download of the image for incorporation into documents or presentations. The interactive components of the chart are shown more fully in the outputs tab above.
Set Up
For this worked example we will investigate the relationship between some income and inequality variables across the Melbourne region.
To do this:
Dataset | Variables |
---|---|
NATSEM – Social and Economic Indicators – Synthetic Estimates SA2 2016 | SA2 Code 2016 |
SA2 Name 2016 | |
Housing Stress (30/40 rule) | |
Poverty Rate (proportion of people with equivalised disposable household income below half median equivalised disposable household income) |
Once you have added these datasets, you are ready to create your scatterplot – click the Inputs tab above to see how to do this