Scatter Plot

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A graph in which the values of two variables are plotted along two axes, the pattern of the resulting points revealing any correlation present.

What is it?

Scatter plots show the relationship between the two variables in pairs of observations.  

In general the Y axis (vertical) contains the outcome, i.e. the measure that you suspect might be influenced by or depend in some way on the measure on the X axis (horizontal).

What does this tool look like?
Visualisation of what the Scatter Plot tool looks like
Why use this tool?

Use a scatter plot if you want to investigate whether or not two variables are related to each other, and also when you want to communicate the nature of a relationship between two measures.

Sometimes it is useful to show a chart that shows no relationship if people have a strong belief or assumption that there is.

Where does this tool fit in the improvement journey?

 

This tool is relevant at this stage of the Quality Improvement Journey.

 

It is also relevant to the three themes that support your journey.

How to use it

How to create it

This is a standard chart in excel.  You need to have two columns of paired data (e.g. data at the same time point or about the same subject). Select the data and choose insert and scatter plot. 

The default is that your first column of data will go on the X axis (horizontal) and your second column will go on the Y axis (vertical), although there is an option in excel (select data) to switch these over.

How to interpret it

If the vertical variable increases as the horizontal one does (as the example above shows) then we can say there is a positive relationship or correlation. This may indicate cause and effect but it may not be that simple.

If the vertical variable decreases as the horizontal one increases we say there is negative relationship or correlation.  This may also suggest a cause and effect relationship for further investigation.

You may also see different patterns, such as a curve showing that there is a relationship that is non-linear.

If the dots are scattered all over the graph with no discernible pattern, then there is no evidence of a relationship between the variables.