Resource Library

This online, interactive lesson on the Poisson process provides examples, exercises, and applets. Specific topics include the exponential distribution, gamma distribution, Poisson distribution, splitting a Poisson process, analogy with Bernoulli trials, and higher dimensional Poisson processes.

This material is a detailed exercise for students in introductory statistics. Students are asked to collect a random sample of data from a real estate website; conduct descriptive statistics (including confidence intervals); and write a report summarizing their dataset. The primary learning goals are to teach students 1) how to obtain a random sample; 2) how to interpret confidence intervals; 3) how to simulate and interpret a sampling distribution; and 4) how to communicate descriptive statistics.

In this free online video program, students will learn that "causation is only one of many possible explanations for an observed association. This program defines the concepts of common response and confounding, explains the use of two-way tables of percents to calculate marginal distribution, uses a segmented bar to show how to visually compare sets of conditional distributions, and presents a case of Simpson's Paradox. The relationship between smoking and lung cancer provides a clear example."

In this free online video program, students will learn that "statistics can be used to evaluate anecdotal evidence. This program distinguishes between observational studies and experiments and reviews basic principles of design including comparison, randomization, and replication. Case material from the Physician's Health Study on heart disease demonstrates the advantages of a double-blind experiment."

This applet shows balls falling through a grid of posts to show the central limit theorem in action.

This chapter of the NIST Engineering Statistics handbook describes Exploratory Data Analysis with an introduction, a discussion of the assumptions, a description of the techniques used, and a set of case studies.

This part of the NIST Engineering Statistics handbook describes different graphs and plots used in Exploratory Data Analysis.

This collection of free, interactive Java applets provides a graphical interface for studying the power of the most commonly encountered experimental designs. Intended to be useful in planning statistical studies, these applets cover confidence intervals for means or proportions, one and two sample hypothesis tests for means or proportions, linear regression, balanced ANOVA designs, and tests of multiple correlation, Chi-square, and Poisson. Each applet opens in its own window with sliders, which are convertible to number-entry fields, for manipulating associated parameters. Controlling for the other parameters, users can change sample size, standard deviation, type I error (alpha) and effect size one at a time to see how each affects power. Conversely, users can manipulate the power for the test to determine the necessary sample size or margin of error. Additional features include a graph option by which the program plots a dependent variable (i.e. power) over a range of parameter values; the graph is automatically updated as the parameters are changed. Each dialog window also offers a Help menu which provides instructions for using the applet. The applets can be used over the Internet or downloaded onto the user's own computer.

One of the goals for the development of the Electronic Encyclopedia of Statistical Examples and Exercises (EESEE) was to provide a wide variety of timely, real examples with real data for use in statistics classes. With each story in EESEE, several thought provoking questions were designed to make students think carefully about statistical issues raised by these applications.

This site is an index of modules which cover probability and statistics topics including basic probability, random variables, moments, distributions, data analysis including regression, moving averages, exponential smoothing, and clustering.