Reusable Z-Test for 1 or 2 Independent Means

Version 5



    There has been a lot of discussion on the forums about getting basic statistical tests into Tableau.  With the assistance of a couple of other members, I was able to create a completely reusable Z-Test which I have found to be faster than using R.  I have an in-depth blog post about using this file (with pictures!) at




    Data set stored in Excel.

    Does not have to be at the appropriate grain.

    The workbook will handle any and all necessary aggregations.




    Open the attached .twbx

    Right-Click the Excel Data Source

    Edit Connection (Change to your Excel Worksheet)

    Edit the following calculated fields:

         Value: The measure you would like to use in your test, along with the aggregation function to be used, such as SUM() or MAX()

         Grain: The dimension of the grain you would like your measure aggregated to.
         Slicer: The dimension you would like to use to create your two samples.

    Use the quick filter on the right side to select which slices you would like to use.

         Selecting 1 slice will compute a 1-sample Z test against the Theoretical Mean Parameter

         Selecting 2 slices will compute a 2-sample Z test.


    That's it.  Your Z-Test has been completed.  Now, you can slice your data any way you would like and can look for any patterns.  I've found that this quite a bit faster than using R to pull in your data, separate it into 2 data sets, then perform the test.




    There is now a 2nd worksheet that allows you to compare the histograms for the two sets of data.  This was not simple and there is a blog post explaining the technique at


    Example Calculation:





    The P-Value formula came from



    Related Calculations:

    Reusable Simple Linear Regression:



    Revision History:


    4/26/2013: Added in-depth blog post for use.

    5/22/2013: Added histograms

    7/3/2013: Added "Related Calculations" Section

                    Updated the workbook to include histogram labels.