Box Plot: Visualizing Distribution and Outliers
What is a Box Plot?
A box plot summarizes a distribution with five numbers: the minimum (whisker end), Q1, the median, Q3 and the maximum; the box spans Q1–Q3 (the interquartile range IQR), whiskers extend to the farthest points within 1.5×IQR, and points beyond are flagged as outliers. The median's position inside the box shows skew and the box width shows dispersion, so one chart condenses the core of a distribution and supports compact comparison of many groups.
When to Use It
Use it to compare distributions across groups (shifts, suppliers, batches), to find outliers quickly, as an overview instead of a histogram for large data sets, and to present distributions to non-statisticians. Because it is robust to outliers, it is a reliable overview even when the data contain anomalies, and it communicates a lot of distribution information in a small space.
How to Use It (Step by Step)
Paste the grouped data and the tool draws and colors a box plot per group, marks outliers, and adds an AI interpretation of the group differences. Compare median positions and heights, box widths (dispersion) and box positions (skew); verify any points beyond the whiskers; non-overlapping boxes usually indicate a meaningful difference between groups.
Key Formulas / Example
IQR = Q3 − Q1; whiskers extend to the most extreme values within [Q1 − 1.5×IQR, Q3 + 1.5×IQR]; points beyond are flagged as outliers. The 1.5 multiplier is a convention and can be adjusted to business rules. For multimodal data, view a histogram alongside, because a box plot alone does not show density or multiple peaks.