Charts & Visualizations

Scatter Plot

A chart that displays the relationship between two numeric variables.

Definition

Scatter plots show the relationship between two variables by plotting data points on a two-dimensional graph, where each point represents an observation with values for both variables.

Examples

Height vs weight correlation

Chart Visualization

This example includes an interactive chart visualization with 4 data points.

Chart type: scatter

Usage

Best Used For

  • Identifying correlations between variables
  • Detecting patterns and clusters
  • Spotting outliers
  • Analyzing distribution of paired data

Data Requirements

[Object]

When to use this chart

Efficiency trade-offs

Data shape: Spend (X) vs iROAS or CPA (Y) per campaign

Reveal outliers and diminishing returns invisible in ranked bar charts

Source: Cleveland & McGill (1984) — position in two dimensions; Few (2009)

Limitations

Important Considerations

  • ⚠Can become cluttered with too many data points
  • ⚠May be difficult to interpret without statistical context
  • ⚠Limited to showing two variables at once without encoding (e.g., size, color)

Best Used For

  • Identifying correlations between variables
  • Detecting patterns and clusters
  • Spotting outliers
  • Analyzing distribution of paired data

Supplemental Resources

Frequently asked questions

Common questions about Scatter Plot, answered.

What is a scatter plot?
A scatter plot maps each data point to a position using two numeric variables — one on the x-axis, one on the y-axis. The resulting cloud of points reveals the relationship between the variables: whether they move together (correlation), form clusters, or contain outliers. It's the go-to chart for exploring how two measures relate, such as ad spend versus conversions across campaigns.
When should I use a scatter plot?
Use one when you want to see the relationship between two continuous variables across many observations — does CPC rise with competition, does watch time relate to conversion rate. Scatter plots excel at exposing correlation, clusters, and outliers that summary statistics hide. Avoid them for categorical comparisons (use bars) or when you have only a few points, where the pattern isn't meaningful.
How do I read correlation in a scatter plot?
Look at the overall shape of the cloud. Points trending up-right suggest positive correlation (as x rises, y rises); down-right suggests negative. A tight band means strong correlation; a diffuse blob means weak or none. A trend line makes the direction explicit. Crucially, correlation isn't causation — a relationship in the points doesn't prove one variable drives the other.
Should I add a trend line to a scatter plot?
Add one when you want to summarize the direction and strength of the relationship, or to make a subtle correlation visible in a noisy cloud. A linear fit is the common default, but match the line to the pattern (it shouldn't be linear if the relationship curves). Always keep the raw points visible — the line is a summary, and hiding the points hides outliers and the true spread.
What's a bubble chart and how is it different from a scatter plot?
A bubble chart is a scatter plot with a third variable encoded as the size of each point. So x and y give position as usual, and the bubble's area shows a third measure — for example x = spend, y = conversion rate, size = revenue. Use a bubble chart when a meaningful third numeric dimension would otherwise be lost; keep it a plain scatter plot when two variables tell the story, since over-sized bubbles can overlap and mislead.

Related Terms

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Data Visualization

Mentioned in

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