### In Tableau, the STDEVP function is an aggregate function used to calculate the population standard deviation of a numeric field within a specified context or group. The population standard deviation measures the dispersion or spread of data points around the mean in the entire population.

The syntax for the STDEVP function in Tableau is as follows:

#### STDEVP(expression)

where the expression is the field or calculation for which you want to calculate the population standard deviation.

Here's an example to demonstrate how to use the STDEVP function in Tableau:

**Suppose you have a dataset that contains information about the test scores of students in a school. You want to calculate the population standard deviation of the scores to understand the variability in the entire student population.**

- Open Tableau and connect to your dataset.
- Drag the "Score" field to the Columns shelf.
- In the Marks card, change the aggregation of the "Score" field to "StDevP" by clicking on the drop-down arrow next to the field and selecting "StDevP." This applies the STDEVP function to the "Score" field and calculates the population standard deviation of the scores.
- Tableau will display the population standard deviation value in the view.

**The result will show you the measure of how the scores deviate from the mean in the entire population. Similar to the sample standard deviation, a higher population standard deviation indicates a greater spread or variability in the scores, while a lower standard deviation indicates a more clustered or consistent set of scores.**

The STDEVP function calculates the population standard deviation without assuming that the data is a sample from a larger population. If you are working with a sample of data, you might consider using the STDEV function instead, which provides an estimate of the standard deviation based on the sample.

In summary, the STDEVP function in Tableau allows you to calculate the population standard deviation of a dataset, providing insights into the variability and dispersion of data points around the mean in the entire population.

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