#### In Tableau, the "COVARP" aggregate function is used to calculate the population covariance between two variables. The population covariance measures the degree and direction of the linear relationship between two variables in the entire population, without relying on a sample.

The syntax of the "COVARP" function in Tableau is as follows:

```
COVARP(expression1, expression2)
```

Here's an example to illustrate how the "COVARP" function works in Tableau:

Suppose you have a dataset of students and their math and science test scores. You want to calculate the population covariance between these two variables.

`COVARP([Math Score], [Science Score])`

In this example, the "COVARP" function is used to calculate the population covariance between the expressions `[Math Score]`

and `[Science Score]`

. It considers the entire population and provides a measure of the linear relationship between the two variables.

The population covariance formula is as follow:

```
COVARP(X, Y) = SUM((X - AVG(X)) * (Y - AVG(Y))) / N
```

In the formula, X and Y represent the variables, AVG(X) and AVG(Y) are the population means, and N is the total number of observations in the population.

The "COVARP" function is useful when you have data for the entire population and want to analyze the relationship between two variables without sampling or estimating.

It's important to note that the "COVARP" function assumes you have the complete population data. If you only have a sample of data and want to estimate the covariance, you would typically use the "COVAR" function, which calculates the sample covariance.

By utilizing the "COVARP" function in Tableau, you can quantitatively assess the covariance between two variables in the entire population, providing insights into their relationship and variability.

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