The Karlin-Rubin theorem provides a test function which has a maximum value for this quantity among probability density functions with the monotone likelihood ratio property.
The Karlin-Rubin theorem provides a test function which has a maximum value for this quantity among probability density functions with the monotone likelihood ratio property. Jacob Cohen wrote a popular book about calculating this quantity while working in the behavioral sciences. The likelihood-ratio test has the highest value of this quantity when testing between two simple hypotheses according to the (*) Neyman-Pearson lemma. Along with significance level, this quantity is decreased when using the Bonferroni correction method and it is often plotted against sample size when designing an experiment. Also known as sensitivity, this quantity is often calculated by finding the probability of not committing a Type II ("2") error. For 10 points, name this statistical quantity defined as the probability of rejecting the null hypothesis when the null hypothesis is false.
The Karlin-Rubin theorem provides a test function which has a maximum value for this quantity among probability density functions with the monotone likelihood ratio property.
statistical power [accept sensitivity before it is read]