Compute the mean of the sample by dividing the sum of the sample values by the number of samples. For example, if our data consists of three values--8, 4 and 3--then the sum is 15 and the mean is 15/3 or 5.

Compute the deviations from the mean of each of the samples and square the results. For the example, we have:

(8 - 5)^2 = (3)^2 = 9 (4 - 5)^2 = (-1)^2 = 1 (3 - 5)^2 = (-2)^2 = 4

Sum the squares and divide by one less than the number of samples. In the example, we have:

(9 + 1 + 4)/(3 - 1) \= (14)/2 \= 7

This is the variance of the data.

Compute the square root of the variance to find the standard deviation of the sample. In the example, we have standard deviation = sqrt(7) = 2.65.

Divide the standard deviation by the square root of the number of samples. In the example, we have:

2.65/sqrt(3) \= 2.65/1.73 \= 1.53

This is the standard error of the sample.

Compute the relative standard error by dividing the standard error by the mean and expressing this as a percentage. In the example, we have relative standard error = 100 * (1.53/3), which comes to 51 percent. Therefore, the relative standard error for our example data is 51 percent.