Sampling and nonsampling error

The quality of the data in a particular survey is a function of what is termed the total survey error. Total survey error reflects the difference between the overall population's true mean value of the characteristic of interest and its mean observed value obtained from the particular sample of respondents. What is of interest is what causes the information obtained from a sample of respondents to differ from that of the entire population. Total survey error is composed of random sampling error and non-sampling error.

Random sampling error occurs because the selected sample is not a perfect representation of the overall population. It represents how accurately the chosen sample's true mean value reflects that of the population. Random sampling error can be controlled by employing an appropriate statistical design and by increasing the sample size.

Non-sampling error represents the extent to which the mean observed value (on the characteristic of interest) for the respondents of a particular sample disagrees with the mean true value for the particular sample of respondents. The size of the non-sampling error depends on two factors: non-response errors and response errors. Non-response errors occur because not all those included in the sample do, in fact, respond. Moreover, the mean true value of those who do not respond may be different from the entire sample's true mean value. Response error, by way of contrast, occurs when respondents give inaccurate answers.

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