Simulation

  • This is a virtual linear regression calculator. It allows students to enter data points, experiment with where the line of best fit might be, and then lets them see the correct line of best fit as well as the outliers. You can click through the introduction.
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  • This section in the Engineering Statistics Handbook takes a data set and walks the user through analysis and experimental design based on the data.
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  • A computer intensive introductory course for graduate students. A veritable online course with Powerpoint and Excel downloadable files for viewing. Also provides related outside links for further investigation on related topics.
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  • The user is be able to change the mean and the standard deviation using the sliders and see the density change graphically. The check buttons (68, 95, 99) will help one realize the appropriate percentages of the area under the curve. An example of thiis "68-95-99.7" rule follows.
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  • This online, interactive lesson on Bernoulli provides examples, exercises, and applets that cover binomial, geometric, negative binomial, and multinomial distributions.
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  • This is the description and instructions for the Two-Dimensional Random Walk applet. This Applet relates random coin-flipping to random motion but in more than one direction (dimension). It covers mean squared distance in the discussion.
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  • This applet is a probabilistic study of picking prizes from an unlimited supply of cereal boxes. The applet helps to answer how many boxes of cereal need to be purchased to have a 50/50 chance of getting all the prizes.
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  • The page will calculate the following: Exact binomial probabilities, Approximation via the normal distribution, Approximation via the Poisson Distribution. This page will calculate and/or estimate binomial probabilities for situations of the general "k out of n" type, where k is the number of times a binomial outcome is observed or stipulated to occur, p is the probability that the outcome will occur on any particular occasion, q is the complementary probability (1-p) that the outcome will not occur on any particular occasion, and n is the number of occasions.

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  • Illustrates the central limit theorem by allowing the user to increase the number of samples in increments of 100, 1000, or 10000.

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  • This page generates a graph of the Chi-Square distribution and displays the associated probabilities. Users enter the degrees of freedom (between 1 and 20, inclusive) upon opening the page.

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