| power.examp {TeachingDemos} | R Documentation |
Create graphs of a normal test statistic under the null and alternative hypotheses to graphically show the idea of power.
power.examp(n = 1, stdev = 1, diff = 1, alpha = 0.05, xmin = -2, xmax = 4) run.power.examp()
n |
The sample size for the test statistic. |
stdev |
The standard deviation of the population. |
diff |
The true difference in means (alternate hypothesis). |
alpha |
The type I error rate to use for the test. |
xmin |
The minimum x value to show on the graph. |
xmax |
The maximum x value to show on the graph. |
This function will draw 2 graphs representing an upper-tailed test of hypothesis.
The upper panel represents the test statistic under the
null hypothesis that the true mean (or mean difference) is 0. It then
also shows the upper tail area equal to alpha and the rejection
region for the test statistic.
The lower panel shows the normal distribution for the test statistic
under the alternative hypothesis where the true mean (or mean
difference) is diff. Using the rejection region from the upper
panel it shades the upper tail area that corresponds to the power of
the test.
Both curves are affected by the specified stdev and sample size
n.
The function run.power.examp will in addition create a Tk
slider box that will allow you to interactively change the values of
stdev, diff, alpha, and n to dynamically
see the effects of the change on the graphs and on the power of the
test.
This can be used to demonstrate the concept of power, show the effect of sample size on power, show the inverse relationship between the type I and type II error rates, and show how power is dependent on the true mean (or difference) and the population standard deviation.
power.examp invisibly returns the power computed.
run.power.examp does not return anything meaningful.
Greg Snow greg.snow@intermountainmail.org
power.examp() power.examp(n=25) power.examp(alpha=0.1)