<P> The formula for the population standard deviation (of a finite population) can be applied to the sample, using the size of the sample as the size of the population (though the actual population size from which the sample is drawn may be much larger). This estimator, denoted by s, is known as the uncorrected sample standard deviation, or sometimes the standard deviation of the sample (considered as the entire population), and is defined as follows: </P> <Dl> <Dd> s N = 1 N ∑ i = 1 N (x i − x _̄) 2, (\ displaystyle s_ (N) = (\ sqrt ((\ frac (1) (N)) \ sum _ (i = 1) ^ (N) (x_ (i) - (\ overline (x))) ^ (2))),) </Dd> </Dl> <Dd> s N = 1 N ∑ i = 1 N (x i − x _̄) 2, (\ displaystyle s_ (N) = (\ sqrt ((\ frac (1) (N)) \ sum _ (i = 1) ^ (N) (x_ (i) - (\ overline (x))) ^ (2))),) </Dd> <P> where (x 1, x 2,..., x N) (\ displaystyle \ textstyle \ (x_ (1), \, x_ (2), \, \ ldots, \, x_ (N) \)) are the observed values of the sample items and x _̄ (\ displaystyle \ textstyle (\ overline (x))) is the mean value of these observations, while the denominator N stands for the size of the sample: this is the square root of the sample variance, which is the average of the squared deviations about the sample mean . </P>

Do i use sample or population standard deviation