Vimal Rajaseharan,
Sabarieswar V.,
- Statistician, Department of Statistics, Psycho Pedagogist and Aviation Expert, Tiruchirappalli, Tamil Nadu, India
- Business Analyst, Department of Statistics, Pedagogist and Aviation Expert, Tiruchirappalli, Tamil Nadu, India
Abstract
A box plot, also known as a box-and-whisker plot, is a widely used statistical graphic that provides a concise summary of the distribution of numerical data. By displaying key descriptive measures such as the median, quartiles, interquartile range (IQR), minimum and maximum values, and potential outliers, box plots allow researchers to quickly understand the spread and central tendency of a dataset. They are especially useful when comparing distributions across multiple groups, as differences in location, variability, and skewness can be identified easily. This paper discusses the construction and interpretation of box plots, emphasizing the significance of their main components. The median indicates the central value of the data, while the quartiles divide the dataset into four equal parts. The interquartile range measures the spread of the middle 50% of observations and helps detect unusual values. Whiskers extend from the box to represent the range of non-outlying observations, whereas outliers are displayed separately to highlight extreme data points. In addition to the traditional box plot, several enhanced versions have been developed to provide further insights into data distributions. Notched box plots incorporate confidence intervals around the median, enabling visual comparison between groups, while violin plots combine box plot features with density estimation to reveal the underlying shape of the distribution. The paper also demonstrates how box plots can be created and customized using the ggplot2 package in R. Through its flexibility and effectiveness, ggplot2 facilitates clear and informative data visualization. Overall, box plots remain an essential tool for exploratory data analysis in statistics, economics, business, and many scientific disciplines.
Keywords: Box plot, quartiles, interquartile range (IQR), outliers, data visualization, ggplot2, r programming, notched box plot, violin plot, exploratory data analysis (EDA)
[This article belongs to Research & Reviews : Journal of Statistics ]
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Research & Reviews : Journal of Statistics
| Volume | 15 | |
| Issue | 02 | |
| Received | 30/05/2026 | |
| Accepted | 03/06/2026 | |
| Published | 15/06/2026 | |
| Publication Time | 16 Days |