Joshua is a graduate student at the USF. He has interests in business technology, analytics, finance, and lean six sigma.
A scatter plot may very well be the most useful creation in the history of statistical graphics. The creation of the scatter plot by Galton led to the use of correlation and regression in the field of statistics.
Scatter plots can tell you a lot about data. Basically, a scatter plot is taking two variables and plotting data points on a graph. Creating a scatter plot in Excel is a great way to find out whether two variables have a relationship and can also measure how close that relationship is.
Below is a data set from an unknown source. Even without discussing background information about the data, it is still possible to figure out how closely related the two variables are within a scatter plot.
Let's run through an example in Excel to highlight the steps used to create a scatter plot.
Inserting a Scatter Plot
To insert a scatter plot, several steps need to be made. First, select the data that you wish to plot. Next, choose the Insert tab and click on the insert scatter or bubble chart option noted by 3 in the illustration below. Finally, select the scatter chart option.
Displaying Chart Elements of a Scatter Plot
Notice the green cross to the right of the scatter chart that appears after the chart is selected. Click on this button to show chart elements options. The list of elements that appear allows you to change the appearance of your graph by adding them to the chart or removing them.
The elements that can be added or removed from a scatter plot are:
- Axis Titles
- Chart Title
- Data Labels
- Error Bars
Any of the above chart element options can be displayed by clicking on the check box next to that option. Each chart element is further explained below.
The axes are shown on the graph by default. You have the option to remove this option if you wish. When the axes are removed, essentially, you are removing the measurements for the X and Y axes.
Show Axis Titles
When axis titles are displayed, the labels can be edited for each axis by double-clicking on these text boxes.
The chart title is set to display by default. This can be removed by unchecking the check box beside "Chart title" or by right-clicking on the chart title and then clicking delete. To edit the title, double-click its text box.
Showing Data Labels
A data labels option is available to show data for each data point. By default, the y-axis position data points are displayed when this option is selected.
Showing Error Bars
Error bars can also be displayed by checking the box next to that option to indicate the uncertainty of data points on the chart.
This option allows you to either add or remove the line in the background of the chart.
Adding the legend allows you to identify the plot point and trendline designs in the chart.
The trendline option will display a trendline based on a regression of all the data In the scatter plot. Sometimes when viewing a scatter plot, the relation between the variables is not apparent. A trendline can tell you three things:
- Whether the data is inversely related when the trendline slants down from left to right.
- whether the data has a direct relationship when the trendline slants up from right to left.
- Whether the data has no relationship when the trendline is a flat line.
Formatting the Trendline
The trendline offers additional options. A few options that can benefit an analysis your data are the options to display the regression equation for the data and R-squared value on the chart. To complete this task, click on the chart, then click on the arrow to the right of the trendline option.
Adding the Slope Equation & R-Squared
To add the regression equation and R-square value click on the check boxes shown in the illustration below.
This content is accurate and true to the best of the author’s knowledge and is not meant to substitute for formal and individualized advice from a qualified professional.
© 2019 Joshua Crowder