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…

Meta-analysis is a collection of systematic techniques for resolving apparent contradictions in research findings. Meta-analysts translate results from different studies to a common metric and statistically explore the relations between study characteristics and findings. Since G. Glass first used the term "meta-analysis" in 1976, it has…

This digest describes the organization of the National Assessment of Educational Progress (NAEP) and what is included in a typical NAEP assessment. The way in which the NAEP selects students for assessments and how the assessments are used are discussed. The NAEP is a congressionally mandated project of the National Center for Education…

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…

Advances in computer technology are making it possible for educational researchers to use simpler statistical methods to address a wide range of questions with smaller data sets and fewer, and less restrictive, assumptions. This digest introduces computationally intensive statistics, collectively called resampling techniques. Resampling is a…

Too few researchers understand what statistical significance testing does and does not do, and consequently their results are misinterpreted. This Digest explains the concept of statistical significance testing and discusses the meaning of probabilities, the concept of statistical significance, arguments against significance testing,…