Calculate Zscores
In statistics, the zscore (or standard score) of an observation is the number of standard deviations that it is above or below the population mean.
To calculate a zscore you must know the population mean and the population standard deviation. In cases where it is impossible to measure every observation of a population, you can estimate the standard deviation using a random sample.
Create a zscore visualization to answer questions like the following:

What percentage of values fall below a specific value?

What values can be considered exceptional? For example, in an IQ test, what scores represent the top five percent?

What is the relative score of one distribution versus another? For example, Michael is taller than the average male and Emily is taller than the average female, but who is relatively taller within their gender?
As a general rule, zscores lower than 1.96 or higher than 1.96 are considered unusual and interesting. That is, they are statistically significant outliers.
This article demonstrates how to calculate a zscore in Tableau.

Connect to the Sample  Superstore data source provided with Tableau Desktop.

Create a calculated field to calculate average sales.
Choose Analysis > Create Calculated Field to open the calculation editor. Name the calculation Average Sales and type or paste the following in the formula area:
WINDOW_AVG(SUM([Sales]))

Create another calculated field to calculate the standard deviation. Name the calculation STDEVP Sales and type or paste the following in the formula area:
WINDOW_STDEVP(SUM([Sales]))

Create one more calculated field, this one to calculate the zscore. Name the calculation Zscore and type or paste the following in the formula area:
(SUM([Sales])  [Average Sales]) / [STDEVP Sales]

Drag ZScore from the Data pane to Columns and State to Rows.
Notice that the Zscore field on Columns has a table calculation icon on the right side (that is, a small triangle):
The STDEVP Sales function is based on the WINDOW_STDEVP function, which is a table calculation function. The ZScore function, in turn, is a table calculation function because it includes STDEVP Sales in its definition. When you use a calculated field that includes a table calculation function in a view, it's the same as adding a table calculation to a field manually. You can edit the field as a table calculation. In fact, that's what you do next.

Click the Zscore field on Columns and choose Compute Using > State.
This causes the zscores to be computed on a perstate basis.

Click the Sort Descending icon on the toolbar:

Hold down the Ctrl key and drag the Zscore field from Columns to Color.
Ctrl + Drag copies a field as currently configured to an additional location.

Ctrl + Drag Zscore from Columns once again. This time drop it on Label.
You now have a distribution of zscores broken out by state. California and New York both have zscores greater than 1.96. You could conclude from this that California and New York have significantly higher average sales than other states.