Quality Assessment for the Evaluation of Sample Size Reduction for Continuous In-Process Data

Abstract

Statistical tests look for evidence that you can reject the null hypothesis and conclude that your program had an effect. With any statistical test, however, there is always the possibility that you will find a difference between groups when one does not actually exist. Power refers to the probability that your test will find a statistically significant difference when such a difference actually exists. In other words, power is the probability that you will reject the null hypothesis when you should. Performing power analysis and sample size estimation is an important aspect of experimental design, because without these calculations, sample size may be too high or too low. If sample size is too low, the experiment will lack the precision to provide reliable answers to the questions that are being investigated. If sample size is too large, time and resources will be wasted, with minimal gain. The purpose of Power Analysis and Sample Size Estimation is to provide you with the statistical methods to answer your questions quickly, easily, and accurately. Key Terms: Continuous In-Process Data, Process Sampling, Sample Power Analysis,Sample Size