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  • This website contains more real analysis, general topology and measure theory than actual probability. It is more about the foundations of probability theory, than probability itself. In particular, it is a very suitable resource for anyone wishing to study the Lebesgue integral. These tutorials are designed as a set of simple exercises, leading gradually to the establishment of deeper results. Proved Theorems, as well as clear Definitions are spelt out for future reference. These tutorials do not contain any formal proof: instead, they will offer you the means of proving everything yourself. However, for those who need more help, Solutions to exercises are provided, and can be downloaded.
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  • This site contains lessons which include steps, examples, and a calculator, on standard deviation, Pearson's r, t-test, one-way ANOVA, and Tukey's Post Hoc Test.
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  • This online, interactive lesson on point estimation provides examples, exercises, and applets concerning estimators, method of moments, maximum likelihood, Bayes estimators, best unbiased estimators, and sufficient, complete and ancillary statistics.
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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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  • Develops the idea of the transition matrix and what it can tell you.
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  • Discusses the benefits of Taguchi methods applied to engineering.
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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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  • 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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  • This site explains small sample hypothesis testing for a normal population and hypothesis testing for a population proportion. Includes examples and exercises.
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  • This site focuses on using the LRT to compare two competing models.
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