Standard Error of Sample-Mean Differences

Standard Error of the Difference Between the Means of Two Samples

The logic and computational details of this
procedure are described in Chapter 9 of
Concepts and Applications.

The difference between the means of two samples, A and B, both randomly drawn from the same normally distributed source population, belongs to a normally distributed sampling distribution whose overall mean is equal to zero and whose standard deviation ("standard error") is equal to

square.root[(sd²/n_a) + (sd²/n_b)]

where

sd² = the variance of the source population (i.e., the square of the standard deviation);
n_a = the size of sample A;

and
n_b = the size of sample B.

To calculate the standard error of any particular sampling distribution of sample-mean differences, enter the mean and standard deviation (sd) of the source population, along with the values of n_a and n_b, and then click the "Calculate" button.


-1sd	mean	+1sd
			<==	source population
			<==	sampling distribution
standard error of sample-mean differences = ±

sd of source population	sd = ±
size of sample A = size of sample B =

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