# Limit Theorems

• ### The Central Limit Theorem in Action

This applet shows balls falling through a grid of posts to show the central limit theorem in action.
• ### Graphical Techniques: By Problem Category (Engineering Statistics Handbook)

This part of the NIST Engineering Statistics handbook describes different graphs and plots used in Exploratory Data Analysis.
• ### Measurement Process Characterization (Engineering Statistics Handbook)

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.
• ### Measurement Process Characterization Case Studies (Engineering Statistics Handbook)

This part of the NIST Engineering Statistics handbook contains case studies for the measurement process chapter.
• ### Production Process Characterization (Engineering Statistics Handbook)

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.
• ### Kolmogorov-Smirnov Goodness-of-Fit Test (Engineering Statistics Handbook)

This page, part of the NIST Engineering Statistics handbook, describes the Kolmogorov-Smirnov goodness of fit test. It contains a graph of the empirical distribution function with the cumulative distribution function, a definition of the test, the questions it answers, the assumptions that it makes, and links to other goodness of fits tests and a case study.
• ### Gallery of Distributions (Engineering Statistics Handbook)

This page, part of the NIST Engineering Statistics handbook, contains links to web pages describing most of the more commonly used distributions.
• ### Process Improvement (Engineering Statistics Handbook)

This chapter of the NIST Engineering Statistics handbook provides information on the proper design of experiments. It contains an introduction, a discussion of assumptions, a description of different design types, a discussion of the analysis of data, and case studies.
• ### Random Samples

This online, interactive lesson on random samples provides examples, exercises, and applets concerning sample mean, law of large numbers, sample variance, partial sums, central limit theorem, special properties of normal samples, order statistics, and sample covariance and correlation.
• ### Belief in the Law of Small Numbers

This journal article gives examples of erroneous beliefs about probability. It specifically examines the belief that a random sample must be representative of the true population.