The Apteo platform allows you to perform some common statistical analysis tasks on your data. The platform currently allows you to perform correlations and statistical t-tests, which come in two formats: the before/after analyzer and the comparison of averages analyzer.
The correlation tool allows you to correlate a primary numerical data series against one or many secondary numerical series. The correlation analyzer will analyze each of your secondary series separately against your primary series, displaying the results of each correlation in a table view and in a graph. To learn more, see the page on Correlations.
Both tools are designed to help you understand whether the average value of two different sets of data are statistically significantly different, but each analyzer accomplishes this using a different worfklow.
The Before/After analyzer is designed to help you measure the change in a KPI after a specific event, date, or change that you specify. It provides options for you to specify how to create the data that will be used to measure those changes.
The Comparison of Averages analyzer is a much simpler tool which allows you to select two numerical columns in your dataset and lets you run a t-test on them to see if their averages are significantly different from each other.