This Digest describes four types of errors in mail surveys and summarizes the ways they can be reduced. Any one of these sources of error can make survey results unacceptable. Sampling error is examined through inferential statistics applied to sample survey results. In general, increasing sample size will decrease sampling error when simple…

Abuses and misuses of statistics are frequent. This digest attempts to warn against these in three broad classes of pitfalls: sources of bias, errors of methodology, and misinterpretation of results. Sources of bias are conditions or circumstances that affect the external validity of statistical results. In order for a researcher to make…

Over the last 15 years or so, research into measurement error has begun to consider not just whether the test items fit, but whether the people who answer the items fit. Attempts to systematically identify people who do not fit the typical pattern have led to several "person-fit statistics." This digest describes the need for such…