Statistical Inference & Techniques

  • 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 random samples provides examples, exercises, and applets concerning sample mean, law of large numbers, sample variance, partial sums, central limit theorem, special properties of normal samples, order statistics, and sample covariance and correlation.
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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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  • This online, interactive lesson on set estimation provides examples, exercises, and applets concerning estimation of the normal model, estimation in the Bernoulli Model, estimation in the two-sample normal model, and Bayesian set estimation.

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  • This online, interactive lesson on hypothesis testing provides examples, exercises, and applets which includes tests in the normal model, Bernoulli Model, and two-sample normal model as well as likelihood ratio and goodness of fit tests.

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  • This site is a collection of Web-enabled scientific services & applications including Equation Plotter Software, Scientific Forecasting Software, Multiple Regression Software, Descriptive Statistics Software, Statistical Hypothesis Testing Software, Sample Size Software, and XML-RPC PHP client.

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  • This set of pages describes software the author wrote to implement bootstrap and resampling procedures. It also contains an introduction to resampling and the bootstrap; and examples applying these procedures to the mean, the median, correlation between two groups, and analysis of variance.
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  • This journal article is a summary of resampling methods such as the jackknife, bootstrap, and permutation tests. It summarizes the tests, describes various software to perform the tests, and has a list of references.
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  • This set of pages is an introduction to Maximum Likelihood Estimation. It discusses the likelihood and log-likelihood functions and the process of optimizing.
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  • This journal article gives examples of erroneous beliefs about probability. It specifically examines the belief that a random sample must be representative of the true population.
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