By Saul McLeod, published 2019

Boxplots are a type of chart often used in explanatory data analysis to visually show the distribution of numerical data and skewness through displaying the data quartiles (or percentiles) and averages.

Minimum ScoreThe lowest score, excluding outliers (shown at the end of the left whisker).

Lower QuartileTwenty-five percent of scores fall below the lower quartile value (also known as the first quartile).

MedianThe median marks the mid-point of the data and is shown by the line that divides the box into two parts (sometimes known as the second quartile). Half the scores are greater than or equal to this value and half are less.

Upper QuartileSeventy-five percent of the scores fall below the upper quartile value (also known as the third quartile). Thus, 25% of data are above this value.

Maximum ScoreThe highest score, excluding outliers (shown at the end of the right whisker).

WhiskersThe upper and lower whiskers represent scores outside the middle 50% (i.e. the lower 25% of scores and the upper 25% of scores).

The Interquartile Range (or IQR)This is the boxplot showing the middle 50% of scores.

Boxplots divide the data into sections that each contain approximately 25% of the data in that set.

Boxplots are useful as they provide a visual summary of the data enabling researchers to quickly identify mean values, the dispersion of the data set, and signs of skewness.

Note the image above represents data which is a perfect normal distribution and most boxplots will not conform to this symmetry (where each quartile is the same length).

The median is the average value from a set of data and is shown by the line that divides the box into two parts. Half the scores are greater than or equal to this value and half are less.

The boxplot shape will show if a statistical data set is normally distributed or skewed.

When the median is in the middle of the box, and the whiskers are about the same on both sides of the box, then the distribution is symmetric.

When the median is closer to the bottom of the box, and if the whisker is shorter on the lower end of the box, then the distribution is positively skewed (skewed right).

When the median is closer to the top of the box, and if the whisker is shorter on the upper end of the box, then the distribution is negatively skewed (skewed left).

In statistics, dispersion (also called variability, scatter, or spread) is the extent to which a distribution is stretched or squeezed.

The smallest value and largest value are found at the end of the ‘whiskers’ and are useful for providing a visual indicator regarding the spread of scores (e.g. the range).

The interquartile range (IQR) is the boxplot showing the middle 50% of scores and can be calculated by subtracting the lower quartile from the upper quartile (e.g. Q3−Q1).

An outlier is an observation that is numerically distant from the rest of the data.

When reviewing a boxplot, an outlier is defined as a data point that is located outside the whiskers of the boxplot.

Source: https://towardsdatascience.com/understanding-boxplots-5e2df7bcbd51

For example, outside 1.5 times the interquartile range above the upper quartile and below the lower quartile (Q1 - 1.5 * IQR or Q3 + 1.5 * IQR).

Box plots are a useful way to visualize differences among different samples or groups. They manage to provide a lot of statistical information, including — medians, ranges, and outliers.

Note, although boxplots have been presented horizontally in this article, it is more common to view them vertically in research papers

Compare the respective medians of each boxplot. If the median line of a boxplot lies outside of the box of a comparison boxplot, then there is likely to be a difference between the two groups.

Source: https://blog.bioturing.com/2018/05/22/how-to-compare-box-plots/

Compare the interquartile ranges (that is, the box lengths), to examine how the data is dispersed between each sample. The longer the box the more dispersed the data. The smaller the less dispersed the data.

Next, look at the overall spread as shown by the extreme values at the end of two whiskers. This shows the range of scores (another type of dispersion). Larger ranges indicate wider distribution, that is, more scattered data.

When reviewing a boxplot, an outlier is defined as a data point that is located outside the whiskers of the boxplot.

If the data do not appear to be symmetric, does each sample show the same kind of asymmetry?

Further Information

McLeod, S. A. (2019, July 19). *Boxplots (also known as box and whister plots)*. Retrieved from https://www.simplypsychology.org/boxplots.html

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