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Design of Experiments

  • A good resource for problems in statistics in engineering. Contains some applets, and good textual examples related to engineering. Some topics include Monte Carlo method, Central Limit Theorem, Risk, Logistic Regression, Generalized Linear .Models, and Confidence.
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  • This site briefly defines several different types of sampling methods, contrasts probability and nonprobability sampling, and discusses target population. Part of a tutorial on questionnaire and survey design.
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  • Discusses the benefits of Taguchi methods applied to engineering.
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  • This Java based applet gives students an opportunity to work through confidence interval problems for the mean. The material provides written word problems in which an individual must be able to correctly identify the given parts for a confidence interval calculation, and then be able to use this information to find the confidence interval. It gives step by step prompts to encourage students to choose the correct numbers and "cast of characters".
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  • This site provides the description and instructions for as well as the link to The Self-Avoiding Random Walk applet. In the SAW applet, random walks start on a square lattice and then are discarded as soon as they self-intersect. If a random walk survives after N steps, we compute the square of the distance from the origin, sum it up, and divide by the number of survivals. This variable is plotted on the vertical axis of the graph, which is plotted to the right of the field where random walks travel.
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  • This is the description and instructions as well as a link for the Forest Fires and Percolation applet. It builds a background with a "hands-on" activity for the students which then leads to the applet itself. The applet is a game where the object is to save as many trees from the forest fire as possible. It shows the spread of a fire with the variable of density and the probabilty of the number of surviving trees.
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  • This section of the Engineering Statistics Handbook describes in detail the process of choosing an experimental design to obtain the results you need. The basic designs an engineer needs to know about are described in detail.
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  • A small collection of applets on the following topics: Introduction to Probability Models, Hypergeometric Distribution, Poisson Distribution, Normal Distribution, Proportions, Confidence Intervals for Means, The Central Limit Theorem, Bivariate Normal Distribution, Linear Regression, Buffon's Needle Problem.
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  • This resource includes problem-based teaching and learning materials for statistics that are based around specific problems arising in biology, business, geography and psychology. The STEPS modules are intended to be used as problem-based lab material that may support existing coursework.
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  • This collection of Analysis Tools can assist students and researchers with questions about study desgin, data analysis, and probability. Topics include sample size, power, survival, binomial probabilities, interaction, Fisher's exact test, one and two sample tests, and more.

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