How to Make a Box Plot for Scientific Papers

A complete guide to creating publication-quality box plots. From statistics to journal-ready export.

What is a scientific box plot?

A box plot (or box-and-whisker plot) is a standardized way of displaying the distribution of data based on a five-number summary: minimum, first quartile (Q1), median, third quartile (Q3), and maximum. In scientific papers, box plots are preferred over bar charts for continuous data because they show the full distribution, not just a mean.

What a box plot shows:

  • Median (line inside the box) — the middle value
  • Box (Q1 to Q3) — the interquartile range (IQR), containing the middle 50%
  • Whiskers — extend to 1.5×IQR from the box edges
  • Outliers — points beyond the whiskers, shown individually
  • Spread — overall range of the data

Step-by-Step Guide

  1. Prepare your data

    Collect replicate measurements for each group. Minimum 5–10 replicates per group for meaningful box plots.

  2. Calculate statistics

    Compute median, Q1 (25th percentile), Q3 (75th percentile), and IQR (Q3–Q1) for each group.

  3. Draw the box

    Draw a box from Q1 to Q3. Add a horizontal line at the median. This is the core of the box plot.

  4. Add whiskers

    Extend whiskers to Q1–1.5×IQR and Q3+1.5×IQR. Mark points beyond as individual outliers.

  5. Label axes

    X-axis: group names. Y-axis: measured variable with units. Ensure labels are readable at journal size.

  6. Export for publication

    Set width to journal column width. Export at 300 DPI. Use a colorblind-friendly palette.

Box Plot vs Bar Chart

AspectBox PlotBar Chart
ShowsDistribution, median, spreadMean, error
Outliers✓ Visible✗ Hidden
Best forContinuous dataCounts, percentages
Journal preferenceIncreasingly preferredStandard but declining

Frequently Asked Questions

How do you make a box plot for a scientific paper?

To make a box plot: (1) collect your data with replicates per group, (2) calculate median, Q1, Q3, and IQR, (3) draw the box from Q1 to Q3 with a median line, (4) add whiskers at 1.5×IQR, (5) mark outliers as individual points, (6) label axes and groups clearly, (7) export at 300 DPI at journal width.

What does a box plot show?

A box plot shows the distribution of data within groups. The box spans the interquartile range (Q1 to Q3), the line inside is the median, and whiskers extend to 1.5×IQR. Outliers beyond the whiskers are shown as individual points. Box plots are ideal for comparing distributions across groups.

When should I use a box plot instead of a bar chart?

Use a box plot when you want to show the distribution of data, not just the mean. Box plots reveal skewness, outliers, and spread. Use a bar chart when you only need to show means with error bars. Many journals now prefer box plots over bar charts for continuous data.

What is the best tool for making box plots?

FigureGuild is ideal for publication-ready box plots. It auto-calculates quartiles, draws whiskers, identifies outliers, and applies journal formatting. R (ggplot2) and Python (matplotlib/seaborn) are also used but require coding. GraphPad Prism supports box plots with a paid license.

Should box plots show individual data points?

Many journals now recommend showing individual data points overlaid on box plots (a "box plot with jitter" or "raincloud plot"). This improves transparency and helps readers assess sample size and distribution shape. FigureGuild supports this overlay style.

How do you interpret whiskers on a box plot?

Whiskers typically extend to 1.5× the interquartile range (IQR) from the box edges. Data points beyond the whiskers are considered outliers. Some software uses different conventions (e.g., whiskers at min/max), so always state the method in your figure legend.

Related Pages

Create Box Plots Automatically

FigureGuild auto-calculates quartiles, draws whiskers, and applies journal formatting — all from your raw data.

Try FigureGuild Free