Returns population covariance, the average of the products of deviations for each data point pair in two data sets.
Use covariance to determine the relationship between two data sets. For example, you can examine whether greater income accompanies greater levels of education.
The COVARIANCE.P function syntax has the following arguments (argument: A value that provides information to an action, an event, a method, a property, a function, or a procedure.):
- Array1 Required. The first cell range of integers.
- Array2 Required. The second cell range of integers.
- The arguments must either be numbers or be names, arrays, or references that contain numbers.
- If an array or reference argument contains text, logical values, or empty cells, those values are ignored; however, cells with the value zero are included.
- If array1 and array2 have different numbers of data points, COVARIANCE.P returns the #N/A error value.
- If either array1 or array2 is empty, COVARIANCE.P returns the #DIV/0! error value.
- The covariance is:
where x and y are the sample means AVERAGE(array1) and AVERAGE(array2), and n is the sample size.
The example may be easier to understand if you copy it to a blank worksheet.
How do I copy an example?
- Select the example in this article. If you are copying the example in Excel Online, copy and paste one cell at a time.
Important: Do not select the row or column headers.
Selecting an example from Help
- Press CTRL+C.
- Create a blank workbook or worksheet.
- In the worksheet, select cell A1, and press CTRL+V. If you are working in Excel Online, repeat copying and pasting for each cell in the example.
Important: For the example to work properly, you must paste it into cell A1 of the worksheet.
- To switch between viewing the results and viewing the formulas that return the results, press CTRL+` (grave accent), or on the Formulas tab, in the Formula Auditing group, click the Show Formulas button.
After you copy the example to a blank worksheet, you can adapt it to suit your needs.
||Covariance, the average of the products of deviations for each data point pair above (5.2)