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How to Compute Standard Error for Sample Sizes

A sample refers to a smaller subsection of an overall population. When you conduct research, you seek to collect data from a sample of the population because it's simply impossible to collect data from every member of a population. Standard error for sample sizes, which is often referred to as sampling error, is a number that "describes the precision of an estimate." Sampling error is typically minimized with a larger sample size. That is, the more people you collect data from, the smaller the sampling error will be.

Calculator
Pen and paper

Instructions

- 1
  Write down the total sample size. This is the total number of cases or people you have collected data from.
- 2
  Calculate the square root of the total sample size. For example, if your total sample size is 100, your square root equals 10.
- 3
  Perform the following calculation: 1 divided by the square root of your total sample size. If we use the example from step 2, we would perform this calculation:
  
  1/10 = .1
- 4
  Multiple the number you calculated in step 3 by 100. The final product is the sampling error. Our example would look like this:
  
  .1 x 100 = 10 percent sampling error

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