This tutorial shows how to easily draw scatter plots in Excel using the XLSTAT software.
Dataset to create a scatter plot
An Excel sheet with both the data and the results can be downloaded by clicking here.
The data correspond to a small group of patients that have been on a specific diet. Their doctor has recorded their Weight before the treatment (kg), how much weight they've lost (kg), if they are satisfied or not with the diet effect, and their "Age".
Our goal is here to visualize the results while keeping as much information as possible.
Setting up a scatter plot
Select the XLSTAT / Visualizing data / Scatter Plot command, or click on the corresponding button of the Visualizing Data toolbar (see below).
Once you have clicked on the button, the Scatter Plot dialog box appears.
In the General tab, select the data on the Excel sheet as following:
- X: Weight;
- Y: Weight loss;
- Z: Age;
- Groups: Satisfied.
In the Options tab, activate the Frequencies and Only if >1 as we want to know if two or more points are superimposed if there is such as case. The Confidence Ellipses option can only be activated if the Z data option is unactivated in the General tab. This tutorial will help you in drawing scatter plots with confidence ellipses in XLSTAT.
Activate the Legend option to be able to identify points belonging to each of the two categories of the Groups column.
Interpreting a scatter plot
Then, after you have clicked on the OK button, a chart is displayed on the sheet starting at H3 (because this cell was selected in the Range option for outputs).
Bubble size is proportional to the Z variable (age in our case) and is thus a way to represent a third dimension on our two-dimensional plot. Here for example, we see that satisfied people are relatively old.
Note 1: for one of the observations a label has been added. This tells us that two observations are surperimposed.
Note 2: the observations labels haven't been used on the chart because the "Observations labels" option was not checked.
Watch the following video for complementary information on scatter plots: