A scatter chart, or a scatter plot is a graph that plots points, or data points, on a coordinate plane. The data points are usually displayed as dots, and the axes represent the two variables being measured. By identifying the trends of the data in a linear or nonlinear form, you can determine whether your data is showing positive or negative results. This is a powerful form of data visualization so that you can see the type of correlation that your data forms. This is a great way of taking large numbers of data points and finding the line of best fit so you can go forward with making informed decisions.
In this article, we’ll go through the steps on how to make a scatter chart.
When To Use a Scatter Chart
Before learning how to make a scatter chart, you may want to know when it’s best to use one. A scatter chart is a graphical tool used to display the relationship between two variables. The dots of the scatter chart will show you a trendline as the dots scatter in a linear or nonlinear path. In other words, it is used to show how much one variable will change when the other variable changes. There are many different situations when a scatter chart can be used, such as:
1. To show the correlation between two variables
2. To show the distribution of data
3. To show the change in one variable when the other variable changes
4. To show the trend of data over time
5. To show the relationship between two categorical variables
6. To identify outliers in data
7. To find the equation of a trendline
8. To investigate the relationship between two continuous variables
9. To find the best-fit line for data
10. To investigate the correlation between two variables with different scales
If any of these situations are what you need, then making a scatter chart can benefit you. It provides a way to look at a set of numerical values at a glance, with various trendline options to make comparisons and inform your decisions. For example, if you’re in the market for a new computer you can use a scatter chart to determine which one is best for your needs.
Making a Scatter Chart
When creating a scatter chart, you must first choose the two sets of data that you will be plotting. This data can be in the form of a table or a list. The x-axis is used to measure the first variable and the y-axis is used to measure the second variable. The x value and y value for their respective axes are added together to create the data points that are shown on the chart. The first column of your table or list should contain the x-coordinates of the points you want to plot, while the second column should contain the corresponding y-coordinates. Your spreadsheet program should be able to automatically create the chart for you after you enter your set of values.
You can go further for your scatter chart and make the data easier to read and understand with colors, fonts, and data labels.
Adding data labels to a scatter chart is a great way to visualize your data. Data labels are the small text boxes that appear next to each data point on a chart. They display the value of the data point.
To add data labels to a scatter chart, you must first select the chart. Then, click on the “Layout” tab and locate the “Data Labels” section. Check the “Show Data Labels” box and then choose how you want Excel or your spreadsheet program to display the values. You can choose from the label position, or where you want your program to place the label; the label orientation, or how you want the labels to line up; then you can change the font and the size of the font for clarity.
You can go further to change the color of the background and the borders settings with a few clicks on the Background tab and border options tab. Once you’ve edited all the chart elements to your liking, you have a scatter chart that will group all of your data variables entered on the XY chart.
Overall, scatter charts are an important tool for data analysis as they allow the user to see relationships between data points. Making a scatter chart is a great first step to visualize your data before you enlist a digital transformation service to build your business, for example. This can be helpful in identifying patterns, trends, and predictions about where your data trendlines will go in the future.