Confidence Intervals  ****
Simulates sampling from a population with a mean of 50 and a standard deviation of 10. The 95% and 99% confidence intervals on the mean are computed.The intervals are displayed graphically and their actually converage can be displayed.

 Confidence Interval Applet  ****
This applet is designed to demonstarte how the confidence intervals are affected by the parameter. Also,You may get a good idea of what a confidence interval really means in terms of covering the true mean.

Confidence Interval on a Proportion  ****
Allows you to explore the validity of confidence intervals on a proportion with  various values of N and Pi.
See also Mean Estimate Experiment, Proportion Estimate Experiment and Variance Estimate Experiment

Power of Hypothesis Test  ****
This applet illustrates the fundamental principles of statistical hypothesis testing through the simplest example: the test for the mean of a single normal population, variance known (the Z test).

The following applets are about hypothesis test
Mean Test Experiment ****
The experiment is to select a random sample of size n from a selected distribution and then test a hypothesis about the mean µ at
a specified significance level. The distribution can be s normal, gamma, and uniform distributions.The test can be constructed under the assumption that the distribution standard deviation is known or unknown.

Proportion Test Experiment  ****
The experiment is to select a random sample of size n from the Bernoulli distribution with parameter p, and then test a
hypothesis about p at a specified significance level.

Sign Test Experiment ****
The experiment is to select a random sample of size n from a distribution, and then to perform a hypothesis test about the
median m of the distribution at a specified significance level.The distribution can be s normal, gamma, and uniform distributions

Variance Test Experiment  ****
The experiment is to select a random sample of size n from a selected distribution and then test a hypothesis about the standard
deviation d at a specified significance level.The test can be constructed under the assumption that the distribution mean is known or unknown