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Google Sheets

STDEV.S is a function in Google Sheets that calculates the standard deviation of a set of values. The standard deviation is a measure of how dispersed the values in a set are from the mean. It is calculated by taking the square root of the variance. The STDEV.S function can be used to calculate the standard deviation of a single column or a range of cells.

The syntax of STDEV.S in Google Sheets is as follows:

=STDEV.S(array)

This function calculates the standard deviation of the values in the supplied array.

The example below shows how to use the STDEV.S function in Google Sheets to calculate the standard deviation of a set of data. In this example, we will calculate the standard deviation of the temperatures in New York City over the past week.

First, we will create a table with the data we want to use in the calculation.

Next, we will use the STDEV.S function to calculate the standard deviation of the data. The function takes five arguments: the range of cells containing the data, the column in the range containing the values we want to calculate the standard deviation for, the name of the column we want to output the standard deviation to, the type of standard deviation we want to calculate (in this case, we want the standard deviation of the values in the column, not the square root of the values), and whether we want to include the values in the calculation or not.

=STDEV.S(A2:A7,2,B2:B7, "std deviation",1)

The function will return the standard deviation of the temperatures in New York City over the past week, which is 5.8 degrees.

STDEV.S should not be used when there are fewer than 10 data points, when the data is not normally distributed, when the sample size is less than 30, or when outliers are present. Additionally, STDEV.S should not be used when the data is not statistically significant.

There are a few similar formulae to STDEV.S in Google Sheets. One is STDEV.P, which calculates the standard deviation of a population. Another is STDEVP, which calculates the standard deviation of a population including the effects of sampling variability. Another is VAR.P, which calculates the variance of a population. Finally, there is VAR.S, which calculates the variance of a sample.

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