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  • This site shows the ISI's alphabetical list of technical terms in statistics showing the translation in a number of languages.
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  • This site gives an explanation, a definition and an example of inference in linear regression. Topics include confidence intervals for intercept and slope, significance tests, mean response, and prediction intervals.
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  • The function of this site is to collect, compile, analyse, abstract and publish statistical information relating to the commercial, industrial, financial, social, economic and general activities and condition of the people.
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  • 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 online introductory statistics textbook covers basic descriptive, statistical, and graphical procedures for analyzing data sets and contains three data sets and a practice final exam. Chapter headings include: Descriptive Statistics, Probability, Resampling, Discrete Probability Models, Continuous Probability Models, Central Limit Theorem, Confidence Intervals, Tests of Hypotheses, Estimation of Effect: Two Independent Samples, Design of Experiments, and Regression. The relation to this site includes exercises.
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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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  • This library contains a plethera of downloadable applets and the components of the applets for use by teachers and students of probability and statistics. These objects (both executable files and source code) can be downloaded, modified if desired, and reused.

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  • This entry in the online encyclopeida, Wikipedia, describes Markov Chains, their properties, discrete state spaces, and formulas for calculating probabilities using Markov Chains. Links to examples and scientific applications are also included.
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