What Are Some Practical Uses for Scatter Plots?

While data is of incredible importance in this era of digital transformation across the economy, it’s also important for business users to be able to understand the information that they’re utilizing. Sometimes, a standard bar chart or pie chart is not enough to truly grasp this insight, and that’s why it’s important to understand some of the better options out there. That’s where a scatter plot may help companies gain better insights.

What is a scatter chart?

A scatter chart, also known as a scatter plot, is a chart that shows a relationship between two variables. It allows viewers to immediately understand a relationship or trend, which would be impossible to see in almost any other form. Scatter plot examples first came to light in the 17th century, becoming common in science journals and publications with the development of the Cartesian coordinates system. Scatter charts have been viewed as the most versatile invention in statistics, providing themselves to be more than just a tool for visualization, but for discovery as well.

A scatterplot is like other graphs in having both an X and Y axes. The X is the horizontal line with the independent variable and the Y is the vertical line with the dependent variable. An even scale is created on both axes, then a mark or dot is made at the point that represents an intersection between these coordinates. Scatter charts also uncover linear correlation through data points. Viewers can also spot weak or strong relationships based on the type of plot. The stronger the correlation is, the closer the dots will be together. A weak correlation will have more data points spread out.

When should companies use scatter plots?

Businesses may decide to use a scatter chart to help them identify anomalies, spotting a sudden sharp transition in a trendline that may have been unanticipated. These plots can also be used to see how one variable affects another and also spot correlations or patterns amongst these datasets. For example, a real estate agent may want to see a relationship between square footage and the price paid for homes. This scatter chart may not drill down all the variables, like renovations or the size of the yard. But it will still give buyers and sellers alike an idea of how the market is functioning.

These charts seek to clearly show the values of individual data points between two variables. With the right formats, any user can visualize trends immediately. As easy as they make data to understand, scatterplots are just as easy to bring to life. These charts also help determine the range of data at a company’s disposal. The maximum and minimum values are important to understand true data value to understand the entirety of the information that is accessible.

What are the best practices for scatter charts?

Creating scatterplots starts with having the Y-axis at zero to avoid any distortion of data. There may be some instances where a scale according is required so that the information is presented accurately. However, it’s important to only use this as needed. No matter the number of points, the scale on a scatter chart should be scaled evenly distributed across both axes. It’s important to recognize outliers within a correlational relationship, excluding them as to not distort the presentation of the data in this plot.

With scatter plots, it’s best to include more data and variables, unlike other chart types. Scatter charts are not confusing with more information, so long as annotations are made by chart creators. It’s important to consider adding size and color variations to dots to emphasize more relevant data across various parameters. The use of trend lines can also be added to make patterns very clear to the viewer. After all, the last thing you want is confusion in the business decision-making process.