Resource Library

This chapter of the NIST Engineering Statistics handbook describes how to do a production process characterization study. It contains an introduction, discussion of the assumptions, information about data collection and analysis, and case studies.

This part of the NIST Engineering Statistics handbook contains case studies for the measurement process chapter.

This chapter of the NIST Engineering Statistics handbook describes the measurement process characterization with discussions of control, calibration, gauge studies, and uncertainty analysis, 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 applet shows balls falling through a grid of posts to show the central limit theorem in action.

This site lists a set of case studies that cover regression topics, random number calculations of pi, as well as limit theorems. On the individual case study pages are the descriptions and/or instructions.

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.

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 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.

This section of ARTIST contains suggestions for implementing student journals, writing assignments, and minute papers in statistics classes. Links to general references for writing assessments are included.