Resource Library

This activity allows the user to create and manipulate histograms with built-in or user-specified data, and provides links to discussion and exercise questions. The mean and standard deviation of each data set are also calculated and the bin width of each histogram can be changed by the user.

This tutorial illustrates the basic principles of the Central Limit Theorem and enhances conceptual understand of why the Central Limit Theorem is important to inferential statistics.

This tutorial takes the learner step-by-step in applying descriptive and inferential statistics using a real world situation.

This site addresses mean, median, mode, bar graphs, pie charts, and line graphs. Each topic has multiple examples with related discussion.

This applet demonstrates probability as the area under the normal and the standard normal curves. Students can manipulate mean, standard deviation, and lower and upper bounds to find probabilities.

This section of the Engineering Statistics Handbook gives the normal probability density function as well as the standard normal distribution equations. Example graphs of the distributions are shown and a justification of the Central Limit Theorem is included.

This simulation applet shows groups of confidence intervals for a given alpha based on a standard normal distribution. It shows how changes in alpha affect the proportion of confidence intervals that contain the mean. An article and an alternative source for this applet can be found at http://www.amstat.org/publications/jse/v6n3/applets/confidenceinterval.html.

The site provides an introduction to understand the basics of and working with Excel. Redoing the illustrated numerical examples in this site will help in improving your familiarity, and as a result, increase the effectiveness and efficiency of your process in statistics.

The applets in this section of Statistical Java allow you to see how the Central Limit Theorem works. The main page gives the characteristics of five non-normal distributions (Bernoulli, Poisson, Exponential, U-shaped, and Uniform). Users then select one of the distributions and change the sample size to see how the distribution of the sample mean approaches normality. Users can also change the number of samples. To select between the different applets you can click on Statistical Theory, the Central Limit Theorem and then the Main Page. At the bottom of this page you can make your applet selection. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/

This applet simulates and plots the sampling distribution of various statistics (i.e. mean, standard deviation, variance). The applet allows the user to specify the population distribution, sample size, and statistic. An animated sample from the population is shown and the statistic is plotted. This can be repeated to produce the sampling distribution of the statistic. After the sampling distribution is plotted it can be compared to a normal distribution by overlaying a normal curve. These features make it useful for introducing students in a first course to the idea of a sampling distribution. The site also includes instructions and exercises. Also available at: http://www.stat.ucla.edu/~dinov/courses_students.dir/Applets.dir/SamplingDistributionApplet.html