Univariate Distributions

  • 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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  • The GAISE project was funded by a Strategic Initiative Grant from ASA in 2003 to develop ASA-endorsed guidelines for assessment and instruction in statistics in the K-12 curriculum and for the introductory college statistics course.
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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 Can You Beat Randomness?- The Lottery Game applet. It is a simulation of flipping coins. Students are asked to make conjectures about randomness and how certain strategies affect randomness. It strives to show the "growth of order out of randomness."
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  • This is the description and instructions for the One-Dimensional Random Walk applet. This Applet relates random coin-flipping to random motion. It strives to show that randomness (coin-flipping) leads to some sort of predictable outcome (the bell-shaped curve).
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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 is the description and instructions for the the Anthill and Molecular Motion applet. Topics include mixing, diffusion, and contour plots.
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  • This site provides the description and instructions for as well as the link to the Diffusion Limited Aggregation: Growing Fractal Structures applet. This applet strives to describe, classify, and measure different random fractal patterns in nature.
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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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