Google Sheets is incredibly popular platform for storing numerical data and information. However, in order to analyze and make sense of this data, it’s important to visualize it in a way that is easy to understand.
One powerful tool for achieving this is the Box and Whisker plot, which is widely used in data analytics due to its ability to quickly identify overall trends in a data set without getting bogged down in unnecessary details.
Despite its usefulness, the Box and Whisker plot is not included in the pre-made plot types available in Google Sheets, which can be frustrating for users.
Still, with a little ingenuity and some clever tricks, it’s still possible to create a Box and Whisker plot using data stored in Google Sheets.
In this article, we’ll explore the Box and Whisker plot in more detail, including how it works and why it’s such a valuable tool for students, researchers, and data scientists alike.
We’ll also delve into the specific techniques and methods that can be used to draw a Box and Whisker, helping you to unlock the full potential of this powerful platform.
Whether you’re a seasoned data analyst or just starting out, mastering the Box and Whisker is an essential skill that can help you take your data analysis to the next level.
What is a Box Plot?
Box plots, also known as Box and Whiskers plots, are a fascinating way to showcase the data on the chart. It’s a powerful tool that helps you understand the distribution of a dataset by dividing it into four quartiles, each containing 25% of the data.
The Box itself represents the middle 50% of the data, with the bottom and top lines representing the first and third quartiles, respectively. The line within the Box denotes the median of the dataset.
The Whiskers of the plot are formed by the minimum and maximum values, which are represented as dots outside the Box, with lines extending to them.
To fully appreciate the insights of a Box plot, it’s essential to understand its key terms. The first quartile is the median of the lower half of the dataset, while the third quartile is the median of the upper half.
The interquartile range is the difference between the first and third quartiles. So next time you encounter a Box plot, you’ll be able to unpack its meaning and gain a deeper understanding of the data it represents.
Box Plot vs. Candle Stick Chart
Box plots and candlestick charts may appear similar at first glance, but they are fundamentally different in their applications. While candlestick charts find frequent use in the finance industry to represent stock prices, Box plots have a much broader range of applications in various industries.
Candlestick charts take on a vertical orientation, resembling the shape of candlesticks, hence their name. On the other hand, Box plots can be displayed either horizontally or vertically and are commonly utilized in analyzing sales performance, inventory, and even sports scores.
Benefits of Using a Box Plot
Box plots are a ubiquitous and valuable tool in the world of analytics and statistics. Out of many, here are some of the key benefits:
- Provides a concise summary of data variation: With just one glance, a Box plot provides a visual representation of how data is spread across a range. This saves time and makes it easier to review large datasets.
- Identifies visual outliers: Unlike other methods of calculating data, such as means, Box plots reveal visual outliers, making them useful for detecting anomalies in a dataset.
- Enables easy comparison of multiple datasets: By generating a visual graph for each dataset and presenting them on a single plot, Box plots make it simple to compare data sets.
- Reveals data symmetry and skewness: The width or narrowness of the Box, and the separation between the Box and the Whiskers, can indicate how skewed or symmetrical a dataset is.
- Similar to a Bell curve: Box plots share many features with a Bell curve, making them an ideal alternative to graphing other datasets.
Given these advantages, Box-and-Whisker plots play a vital role in data analytics, especially in fields such as scientific research. With their ability to concisely summarize and visualize complex data, Box plots are a powerful tool that anyone working with data should know how to use.
- Also read: Box and Whisker Plots in Excel
How to Create Box and Whisker Plot in Google Sheets?
The process of creating a Box plot in Google Sheets is a easy.
Highlight the quartile data on the Google Sheets and select Charts from the Insert option.
And it will automatically suggest you the chart according to your data. Otherwise, from the Chart editor, select Candlestick chart.
Although we’ve discussed above that the candlestick charts are different from Box plots, these are the only alternative option to display the data in Google Sheets.
Making Multiple Box and Whisker Charts at Once
You can follow the above steps and simply highlight a larger collection of data. Let’s take a look at the data set below.
As you can see in the screenshot, we’ve already highlighted the data. Now all we have to do is:
- Insert a chart
- Change it to a candlestick chart.
When to Use Box and Whisker Chart?
Box and Whisker chart is a powerful tool for visualizing data when you have multiple independent data sets that are somehow related. This chart type is particularly useful in many practical scenarios, some of which are listed below:
- When you need to compare the performance of the same machines manufacturing the same products in a factory.
- When you want to analyze and compare test scores between different classes or educational institutions.
- When you need to examine and compare data before and after a significant process change in a company.
By using Box and Whisker Plots, you can easily identify patterns and trends in the data that might not be visible through other visualization techniques. So if you’re dealing with multiple relevant data sets and won’t want to add meaning to them, consider using Box and Whisker Plots.
When Shouldn’t You Use a Box and Whisker Chart?
- The Box and Whisker Plot is designed to provide a summary of your dataset and does not hold the exact values of your data.
- While the chart can be helpful for understanding the distribution of your data, it may confuse people who are not familiar with statistics such as standard deviation and quartiles.
- It’s essential to keep in mind that the Box and Whisker Plot is just one tool in a data analyst’s toolkit and should be used in conjunction with other methods to get a complete picture of the data.
By understanding the limitations and potential confusion surrounding the Box and Whisker Plot, you can avoid misinterpreting your data and present it in a clear and meaningful way to your audience.
So, it’s always a good idea to provide additional context and explanation to help your audience fully understand the information you are presenting.
FAQs
Why are Box Plots used for visualizing small data sets?
When working with small data sets, the Box and Whisker Plot can effectively display key descriptive insights such as the mean, median, standard deviation, maximum and minimum values, and quartiles.
Can we use Box plots for comparing different samples?
The Box and Whisker Chart is an ideal tool for representing diverse data sets, using its ‘five-number summary’ to reveal valuable insights such as range, quartiles, and mean. This chart is popular in numerous fields, including education, research, and agriculture, for comparing different samples.
What is a Box and Whisker plot in layman’s terms?
The Box and Whisker Plot, commonly referred to as the Box Plot, is a powerful visualization tool that leverages Japanese candle shapes to provide valuable insights into complex data sets.
This design is perfect for presenting a bird’s eye view of your data, highlighting key statistics such as mean, median, quartiles, and standard deviation.
With its ability to display essential information in a concise and intuitive manner, the Box Plot is an indispensable asset for anyone looking to gain deep insights into their data.
To Conclude
Box and Whisker plots are an effective method of visualizing data that enables a user to identify overall trends quickly. Although not included in the pre-made plot types available in Google Sheets, it is still possible to create a Box and Whisker plot using data stored on these platforms.
Box and Whisker plots are often used in various industries for sales performance analysis, inventory, and even sports scores, among others.
They provide a concise summary of data variation, identify visual outliers, enable the easy comparison of multiple datasets, reveal data symmetry and skewness, and are similar to a Bell curve.
So, if you are a Google Sheets user, now you have the step-by-step guide to creating Box plots for your data.