Moreover, the box plot can be quite helpful in understanding the distribution and range of data. These limitations aside, if your data is more or less symmetrically distributed around the median, then the box plot can help you understand the distribution at a glance, even if you have a really large dataset. might not be able to understand or interpret a box plot correctly. So, people who are not really familiar with concepts like quartiles, etc. Box plots are not very intuitive at first glance.The box plot is good at representing bell shaped or Gaussian distributions, but can hide certain important insights in case of bimodal or other non-Gaussian distributions.There are a few points to note about box plots: Here are the formulas that we used for our sample dataset: Step 1: Compute the 5 Summary Descriptors from the Dataįirst, we need to compute the 5 summary descriptors.įor this, create a second table based on the main data, using the formulas shown below (Make sure they are in the same order as shown below too): Descriptor
How to make box and whisker plot in excel how to#
Let us see how to perform each of these steps in more detail.
Up until Excel 2016, there was no separate feature in Excel to create box plots.Īs such, in older versions, if you need to create a box plot, you need to improvise a stacked chart and convert it into a box plot. Now that we understand box plots a little better, let us see how to create them in Excel. From the above chart we can see that the highest salary paid by the company is $10,000. The tip of the bottom whisker marks the minimum value in the data (or the lowest salary paid by the company).This also helps us see if the dataset is skewed. The length of the bottom whisker represents how far the lowest value is from the median of the dataset.In the above chart, we can see that the range of salaries is 40,000-10,000 = $30,000. In other words, it tells us if there is a large amount of variation in employee salaries or if they are more or concentrated around the median. The vertical width of the box represents the spread in the data.The line that runs across the middle of the box is the second quartile or the median value of the data.The bottom edge of the box marks the first quartile of the data.The top edge of the box marks the third quartile of the data.This value can help us identify if the dataset is skewed or if there are any potential outliers. The length of the top whisker represents how far the highest value is from the median of the dataset.From the above chart we can see that the highest salary paid by the company is $40,000. The tip of the top whisker (line) marks the maximum value in the data.Let us interpret this chart by looking at its 5 indicators: The image below shows employee salaries of a given company: How to Interpret a Box Plotīefore we see how to create a box plot (also called a box and whisker chart), let us first learn to understand and interpret a box plot. In this way, box plots also help us find outliers and can tell if the data is symmetric or skewed.īox plots are especially helpful when you want to compare different sample distributions, and since it provides a 5-point summary of the entire dataset, it is really useful when the datasets you are studying are very large. They can be quite helpful when you want to see how the data is distributed and the range to which the data extends. Why Use a Box Plot?Ī box plot is a great way to visually summarize your data using 5 descriptive indicators. The width of the box basically marks the most concentrated area of the data distribution.Ī box plot can also contain ‘whiskers’ which are simply lines that depict the minimum and maximum values that are outside the first and third quartiles. The main ‘box’ of the box plot is drawn between the first and third quartiles, with an additional line drawn to represent the second quartile, or the ‘median’. The box plot divides numerical data into ‘quartiles’ or four parts. An example of a Box Plot chart created in Excel
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