Resource Library

A thesis written on the topic of statistical quality control that provides good information about the history and use of SQC.

Resource that gives a definition, objectives, tools for statistical quality control.

A resource providing information about what the sample size is, what factors the sample size depends on, and how it can be determined,

Provides a link that leads to a direct download of a powerpoint about statistical quality control.

Resource providing information about: computation of the sample size and the assumptions that must be made to do so. Several examples are given with different conditions in each, and a table showing minimum sample sizes for a two-sided test.

Article that explains why comparing statistical significance, sample size and expected effects are important before constructing and experiment.

If you plan to use inferential statistics (e.g., t-tests, ANOVA, etc.) to analyze your evaluation results, you should first conduct a power analysis to determine what size sample you will need. This page describes what power is as well as what you will need to calculate it.

Determining the right sample size in a reliability test is very important. If the sample size is too small, not much information can be obtained from the test in order to draw meaningful conclusions; on the other hand, if it is too large, the information obtained through the tests will be beyond that needed, thus time and money are wasted. This tutorial explains several commonly used approaches for sample size determination.

The process of sample size calculations, including relevant definitions, is explained and clear examples for different study designs are provided for illustration. A range of software packages and websites are discussed and evaluated

Chapter from a textbook that covers the topic of sample size by giving a thorough background and then covering issues that are involved when determining the sample size.