College --Undergrad Lower Division

  • This site offers a collection of applets in which standard topics of statistics and probability are presented in a novel and visual way using computer animated images. Topics include dependence, independence, conditional probabilities, expectation and variance, normal, exponential, Poisson distributions, law of large numbers and the central limit theorem, hypothesis testing maximum likelihood estimation, sampling, chi-square tests, and the construction of confidence intervals.
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  • This applet is a probabilistic study of picking fortunes from a limited supply of fortune cookies. The student will try to answer how many cookies he/she has to eat to have a 50/50 chance of reading all the fortunes.
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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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  • Here one finds a collection of applets and famous problems in probability (as well as other areas of mathematics such as calculus and geometry). Some of the topics/problems include: Bertrand's Paradox, Birthday Coincidence, Buffon's Needle (Noodle), Lewis Carroll's Problem, Monty Hall Dilemma, Parrondo Paradox, and Three pancakes problem.

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  • This website provides lesson plans, activities, a problem bank, and links to references that meet NCTM standards for probability.
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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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  • 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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  • This page calculates the standard error of a sampling distribution of sample means when users input the mean and standard deviation of the population and the sample size.

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