; PSY 1903
PSY 1903 Programming for Psychologists

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Good Plotting Practices in Scientific Work

High-quality figures do more than make your work look polished. They help readers understand your results quickly and accurately. Strong visualizations support your research question, clarify patterns in your data, and align with scientific communication standards.

This reference outlines core principles you can apply to any plot you make, whether exploratory or for a final report. The goal is to help you produce figures that are clear, readable, and meaningful.

1. Use Descriptive Labels

A good plot explains itself without requiring the reader to dig through your text or code.

  • Always label axes clearly.
  • Include units whenever possible (“Reaction Time (ms)”).
  • Replace internal variable names with human-readable descriptions.
  • Avoid vague labels like “Value,” “Measure,” or “Score,” unless your audience knows exactly what they refer to.

Readable labels help your reader understand what is being measured and why it matters.

2. Keep Titles Short but Informative

A title should tell the reader what the plot shows, not what the results mean.

Good title:
“Mean Reaction Time by Focus Group”

Not ideal:
“High Focus Participants Show Slower Reaction Times on Average”

Your title introduces the figure. Your interpretation belongs in the surrounding text or caption.

3. Limit Unnecessary Decoration

Simple plots are almost always easier to interpret.

  • Avoid 3D bars, gradient backgrounds, shadows, or heavy outlines.
  • Use color purposefully. If color is not communicating information, remove it.
  • Do not overload the plot with patterns or excessive annotations.

The goal is clarity, not decoration.

4. Use Color Intentionally (and Sparingly)

Color can be a powerful tool, but only when used thoughtfully.

  • Use color to indicate meaning: groups, conditions, or levels of an independent variable.
  • Avoid using many colors when two or three will do.
  • Consider accessibility: avoid red/green combinations unless the distinction is clear for most viewers.
  • Keep the same colors consistent across all figures in a report.

If color does not strengthen the figure’s message, do not use it.

5. Maintain Consistency Across Figures

Readers should not have to mentally re-adjust for each figure.

  • Keep text sizes similar across plots.
  • Use the same theme or a variation of one theme.
  • Use the same ordering of factor levels across all figures.
  • Keep color assignments consistent.

Consistency reduces cognitive load and helps the reader follow your narrative.

6. Make Sure Scales Support the Message

The scale should help readers interpret the data correctly.

  • For bar plots, the y-axis should usually start at zero.
  • For scatterplots or histograms, axis limits should cover the full range of the data unless you have a clear reason not to.
  • Avoid overly compressed or stretched axes.
  • If you truncate an axis, explain why in the caption or surrounding text.

Scales influence how patterns are perceived. Choose them deliberately.

7. Reduce Noise and Improve Readability

A figure should make it easy to identify patterns.

  • Remove gridlines you do not need, especially minor ones.
  • Keep major gridlines light and unobtrusive.
  • Avoid overlapping labels.
  • Use horizontal orientation (coord_flip) for long category names.
  • Use jittered points to avoid overplotting.

Simplicity often improves clarity.

8. Support Your Research Question

Plots are not decoration. They serve a purpose.

Good figures help you:

  • explore your data,
  • communicate findings,
  • evaluate hypotheses,
  • and guide interpretation.

A figure should help you and your reader see how the data relate to the research question.

9. Provide Clear Captions

A well-written caption helps situate the figure.

A good caption includes:

  • what is being shown,
  • the groups or variables included,
  • any essential statistical references,
  • a brief description of what to look for.

Captions do not interpret results; they describe the plot so the reader can interpret it themselves.

10. Prioritize Accessibility and Reproducibility

  • Use readable fonts and color values that reproduce well in grayscale.
  • Choose themes that export cleanly to PDF and PNG.
  • Save figures with consistent dimensions.
  • Include code that produces the full figure within your Quarto documents.

Good figures should be easy to reproduce exactly.

Summary

Good plots are clear, honest, and purposeful.
They help readers understand your results and support your research goals.

Keep asking yourself:

“Does this figure help the reader understand what the data are saying?”

If the answer is yes, your visualization is on the right track.