For many data distributions, it is often handy to have more metrics than the central tendency measure of median, mean, and mode. It is often handy to have insights concerning the variability or dispersion of the data. A boxplot is a graphical method that shows how the values in the data are distributed.
Boxplots are useful when comparing distributions between many groups, data sets, or (with the case of Survey2Persona), survey questions.
Boxplots are a standardized way of displaying the distribution of data based on eight attributes (Median, Minimum, 1st quartile [Q1], 3rd quartile [Q3], Interquartile Range, Whiskers, Outliers, and Maximum).
- Median (Q2/50th percentile) – the middle value of the data set
- First Quartile (Q1/25th percentile) – the middle number between the smallest number (not the minimum) and the median of the data set
- Third Quartile (Q3/75th percentile) – the middle value between the median and the highest value (not the maximum) of the dataset
- Interquartile Range (IQR) – 25th to the 75th percentile
- Whiskers – indicate variability outside the upper and lower quartiles
- Outliers – an observation that is numerically distant from the rest of the data
- Maximum – Q3 + 1.5*IQR
- Minimum – Q1 -1.5*IQR
Here is an example of a boxplot in Survey2Persona:
Example of a boxplot in Survey2Persona
For more on Survey2Persona, read:
Jung, S.G., Salminen, J. and Jansen, B. J. (2022) Survey2Persona: Rendering Survey Responses as Personas. UMAP ’22 Adjunct: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, 4-7 July, Barcelona (Spain), p. 67–73.
