Sometimes more than one test statistic is used to conduct a hypothesis test. In this case the relative power of the test needs to be computed for the competing statistics; the test statistic that is

If you want to know more about "power of a test," read the following (not required for Level I candidates):

Consider a hypothetical experiment designed to test whether rats brought up in an enriched environment can learn mazes faster than rats brought up in the typical laboratory environment (the control condition). Two groups of 12 rats are tested. Although the experimenter does not know it, the population mean number of trials it takes to learn the maze is 20 for rats from the enriched environment and 32 for rats from the control condition. The null hypothesis that the enriched environment makes no difference is therefore false.

The question is,

It is important to keep in mind that power is not about whether or not the null hypothesis is true (it is assumed to be false). It is the probability the data gathered in an experiment will be sufficient to reject the null hypothesis. The experimenter does not know that the null hypothesis is false. The experimenter asks the question:

If the experimenter discovers that the probability of rejecting the null hypothesis is low (power is low), even if the null hypothesis is false to the degree expected (or hoped for), then it is likely that the experiment should be redesigned. Otherwise, considerable time and expense will go into a project that has little chance of being conclusive even if the theoretical ideas behind it are correct.

tomalot: Not required for Level 1...SKIP! |