Scatter graphs, or scatter diagrams, look at a possible correlation between two variables. Large amounts of data are usually recorded to investigate trends, and scatter graphs are particularly useful for analysing this kind of data.
Scatter graphs enable correlations between disease and lifestyle choices, and correlations between disease and environmental or industrial conditions, eg possible effects of pesticides, industrial chemicals, etc.
It is also a good way of looking at trends across different countries.
The scatter graph below uses data from a landmark scientific paper of 1975, where Ken Carroll investigated women eating different amounts of animal fat and deaths from breast cancer.
Each data point represents a piece of data from a different country.
The data shows a clear trend between animal fat intake and death rates from breast cancer.
If a scatter graph does show a correlation between two sets of data, a line of best fit can be added to illustrate the trend.