STDEV
The STDEV function returns the standard deviation — a measure of dispersion — of a set of numeric values based on their sample (unbiased) variance.
STDEV(value, value…)
value: A number value, date/time value or duration value, or collection of these value types. All values must be of the same value type and a minimum of two values is required.
value…: Optionally include one or more additional values or collections of values.
Notes
It is appropriate to use STDEV when the specified values represent only a sample of a larger population. If the values you are analysing represent the entire collection or population, use the STDEVP function.
The standard deviation is the square root of the variance returned by the VAR function.
Examples |
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Suppose you administered five tests to a group of students. You arbitrarily selected five students to represent the total population of students (note this is an example only; this would be unlikely to be statistically valid). Using the sample data, you could use the STDEV function to determine which test had the widest dispersion of test scores. This might be useful in determining lesson plans, identifying potential problem questions or for other analysis. You enter the test scores into a blank table, with the scores for each student in the sample in columns A to E and the five students in rows 1 to 5. The table would appear as follows. |
| A | B | C | D | E |
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1 | 75 | 82 | 90 | 78 | 84 |
2 | 100 | 90 | 95 | 88 | 90 |
3 | 40 | 80 | 78 | 90 | 85 |
4 | 80 | 35 | 95 | 98 | 92 |
5 | 90 | 98 | 75 | 97 | 88 |
=STDEV(A1:A5) returns approximately 22.8035085019828, the standard deviation of the results of Test 1. =STDEV(B1:B5) returns approximately 24.5356882927706, the standard deviation of the results of Test 2. =STDEV(C1:C5) returns approximately 9.50263121456368, the standard deviation of the results of Test 3. =STDEV(D1:D5) returns approximately 8.07465169527454, the standard deviation of the results of Test 4. =STDEV(E1:E5) returns approximately 3.3466401061363, the standard deviation of the results of Test 5. Test 2 had the highest dispersion (standard deviation is a measure of dispersion), followed closely by Test 1. The other three tests had lower dispersion. |
Example — Survey results |
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To see an example of this and several other statistical functions applied to the results of a survey, see the COUNTIF function. |