Identify the statistic whose standard error you need (mean, proportion, regression coefficient, etc.).
Determine the formula for standard error based on the statistic:
Standard error of the mean: (SE=dfrac{s}{sqrt{n}})
Standard error of the mean using population SD: (SE=dfrac{sigma}{sqrt{n}})
Standard error of a proportion: (SE=sqrt{dfrac{hat{p}(1-hat{p})}{n}})
Standard error of a difference in means: (SE=sqrt{dfrac{s_1^2}{n_1}+dfrac{s_2^2}{n_2}})
Standard error of a difference in proportions: (SE=sqrt{dfrac{hat{p}_1(1-hat{p}_1)}{n_1}+dfrac{hat{p}_2(1-hat{p}_2)}{n_2}})
Collect the required inputs:
(n) (sample size)
(s) (sample standard deviation) or (sigma) (population SD, if known)
(hat{p}) (sample proportion) for proportions
(s_1, s_2, n_1, n_2) for differences in means
Substitute values into the appropriate standard error formula.
Compute the standard error.
If using regression output:
Take the reported “Std. Error” for the coefficient from the regression summary table.