A scatter plot is the best graph for showing the relationship between two quantitative variables.

Why a scatter plot?

  • Each point represents one observation, with one quantitative variable on the x-axis and the other on the y-axis.
  • It lets you see patterns like:
    • Whether the relationship is positive, negative, or absent
    • Whether it looks linear or curved
    • How strong or weak the association is
    • Outliers or unusual points

Quick comparison with other graphs

  • Bar charts: Better for comparing categories , not two numeric variables.
  • Histograms: Show the distribution of a single quantitative variable, not a relationship.
  • Pie charts: Show parts of a whole, not variable relationships.
  • Line graphs: Good for trends over time, but not the default for general two-variable relationships.

Mini example

Imagine you have ā€œhours studiedā€ and ā€œtest scoreā€ for 50 students. Plot hours on the x-axis and score on the y-axis. Each student is one dot. If dots rise up as you move right, you see that more study hours tend to go with higher scoresā€”thatā€™s exactly the kind of relationship a scatter plot is designed to reveal.

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Learn what type of graph is best for showing the relationship between two quantitative variables, why scatter plots are ideal, and how they compare to bar charts, histograms, and line graphs.