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Examples of how to use z-test functions

The z-test functions are used to find values associated with z-test statistical analysis for large data samples, usually greater than 30, and where the variance is known.

This section describes how to build visualizations using sample data to find the values of the z-test functions available in Qlik Sense. Please refer to the individual z-test chart function topics for descriptions of syntax and arguments.

Loading the sample data

The sample data used here is the same as that used in the t-test function examples. The sample data size would normally be considered too small for z-test analysis, but is sufficient for the purposes of illustrating the use of the different z-test functions in Qlik Sense.

Do the following:

  1. Create a new app with a new sheet and open that sheet.
  2. Tip noteIf you created an app for the t-test functions, you could use that and create a new sheet for these functions.
  3. In the data load editor, enter the following:


    crosstable LOAD recno() as ID, * inline [





















    25|2 ] (delimiter is '|');

    In this load script, recno() is included because crosstable requires three arguments. So, recno() simply provides an extra argument, in this case an ID for each row. Without it, Comparison sample values would not be loaded.

  4. Click run script to load data.

Creating z-test chart function visualizations

Do the following:

  1. In the data load editor, click compass to go to app view, and then click the sheet you created when loading the data.

    The sheet view is opened.

  2. Click Edit sheet to edit the sheet.
  3. From Charts add a table, and from Fields add Type as a dimension.
  4. Add the following expressions to the table as measures.

  5. Example expressions
    Label Expression
    ZTest Conf ZTest_conf(Value)
    ZTest Dif ZTest_dif(Value)
    ZTest Sig ZTest_sig(Value)
    ZTest Sterr ZTest_sterr(Value)
    ZTest Z ZTest_z(Value)
Tip noteYou might wish to adjust the number formatting of the measures in order to see meaningful values. The table will be easier to read if you set number formatting on most of the measures to Number>Simple, instead of Auto. But for ZTest Sig, for example, use the number formatting: Custom, and then adjust the format pattern to # ##.


The resulting table for the z-test functions for the sample data will contain the following values:

Results table
Type ZTest Conf ZTest Dif ZTest Sig ZTest Sterr ZTest Z
Comparison 6.40 11.95 0.000123 3.27 3.66
Value 5.48 27.15 0.001 2.80 9.71

Creating z-testw chart function visualizations

The z-testw functions are for use when the input data series occurs in weighted two-column format. The expressions require a value for the argument weight. The examples here use the value 2 throughout, but you could use an expression, which would define a value for weight for each observation.

Examples and results:  

Using the same sample data and number formatting as for the z-test functions, the resulting table for the z-testw functions will contain the following values:

Results table
Type ZTestw Conf ZTestw Dif ZTestw Sig ZTestw Sterr ZTestw Z
Comparison 3.53 2.95 5.27e-005 1.80 3.88
Value 2.97 34.25 0 4.52 20.49

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