This is the 2007 version. Click here for the 2017 chapter 01 table of contents.

Sampling Error

Assuming you do have a truly random sample, the accuracy of the sample (for purposes of representing the larger population) can be calculated and expressed as sampling error. Sampling error is the amount of error one might expect, based upon the size of a random sample.

What is the "margin of error"?

You have probably seen sampling error reported in poll results. For example, a poll might show that candidate A has the support of 43% of the population "plus or minus 3%." The plus or minus 3% is the sampling error, often called the margin of error. A poll result of "43% plus or minus 3%" usually means, "With 90% likelihood the true figure for the entire population is between 40% and 46%." The concept of sampling error is based on the ideal of a random sample. In a truly random sample, everybody in the target population has an equal chance to be included in the sample. As long as that condition is met, scientists can calculate the margin of error or expected accuracy of the sample.

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