The standard deviation is the square root of the variance returned by the VARPA function.
Example
Suppose you installed a temperature sensor in a house in California. The sensor records each day’s high and low temperatures in degrees Fahrenheit. The data from the first few days of July is shown in the following table and is used as a sample for the population of high and low temperatures (note that this is an example only; this would not be statistically valid). On July 5, the sensor failed, so the data in the table shows n/a, or not available.
A
B
C
1
Date
High
Low
2
01/07/2010
58
3
02/07/2010
84
61
4
03/07/2010
82
59
5
04/07/2010
78
55
6
05/07/2010
n/a
7
06/07/2010
81
57
8
07/07/2010
93
67
=STDEVPA(B2:B8) returns approximately 29.4472894702188, the dispersion (standard deviation is a measure of dispersion) as measured by STDEVPA, of the sample of daily high temperatures.
If you had a large data set that could not easily be visually scanned, or you wished to automate checking for missing values, you could compare the results of=STDEVP(B2:B8), which returns approximately 10.6092203085597, and STDEVPA, which returns approximately 29.4472894702188. If (as in this case) they are not equal, it would indicate the data set contains text (such as "n/a"), or one or more boolean values (TRUE or FALSE).