Overview: Statistical power is the probability of correctly
rejecting a false null hypothesis when a specific alternate hypothesis
is true. For example, the ACE training program boasts that their graduates score
higher on a standardized test than the population of individuals who do
not participate in their training course. Power analysis allows us to
determine how likely it is that a test of statistical significance such
as a z-test will support the claims of the training program. We also can
determine how many cases we need in our sample to attain a specific
level of statistical power.
What will I learn? You will learn how statistical power is
influenced by four features of the test situation: the size of the
difference between the actual population mean and the null hypothesized
mean (μ1 – μ0); variability
of scores within groups (s); sample size
(N); and alpha error (a).
You will use an interactive applet that allows
you to manipulate features of the test situation and immediately see the
effect on statistical power.
What do I need to know? You should have an
understanding of hypothesis testing concepts and procedures. You may want to complete
the WISE Hypothesis
Testing Tutorial prior to the power tutorial. The examples in this
power tutorial are similar to those used in the hypothesis testing
What do I need? For this tutorial you will need a
paper copy of the WISE Power Lab exercise pages and access to the WISE
Power applet. If you do not have a copy of the lab exercise, click
for a printable version of the whole tutorial and or just the
to write down your answers.
Instructions: You will be asked to use the Power applet to
simulate sampling data in different situations. You will record data and then interpret your findings in terms of statistical
power. Along the way you will be asked questions to test your
understanding and you will be given feedback regarding your answers. The
end of the tutorial includes some "thought" questions.
Optional review material (one page each):
Begin the Power Tutorial.
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