A scatter plot is a plot of two variables, X and Y, measured independently to produce bivariate pairs (Xi, Yi), and displayed as individual points on a coordinate grid typically defined by horizontal and vertical axes, where there is no necessary functional relation between X and Y.<\/p>\n
Use the scatter plot if you:<\/p>\n
Even if there is a correlation between two variables, we cannot conclude that one variable causes a change in the other. This relationship could be coincidental, or other factors that aren’t being plotted may be causing either or both variables to change.<\/p>\n
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To avoid this, you can try changing the scatter plot into a diamond plot.<\/p>\n
If a correlation is found, it will be a mix of the following:<\/p>\n
Note<\/strong>: if no correlation is found, especially if you are expecting one, consider whether the independent (x-axis) variable has been varied widely. Sometimes a relationship is not apparent because the data do not cover a wide enough range.<\/p>\n Main takeaways:<\/strong><\/p>\n More related to it than a type of: <\/p>\n Trend line<\/strong><\/p>\nHistory of the Scatter Plot<\/h2>\n
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Types of Scatter Plots<\/h2>\n
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Visualization Best Practices<\/h2>\n