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 Markov Chains Created by Kyle Siegrist of the University of Alabama-Huntsville, this is an online, interactive lesson on Markov chains. The author provides examples, exercises, and applets to introduce the subject. More specifically, the lesson covers: recurrence, transience, periodicity, time reversal, as well as invariant and limiting distributions. In addition, the author has provided links to external... http://www.math.uah.edu/stat/markov/index.html
 Geometric Models Created by Kyle Siegrist of the University of Alabama-Huntsville, this is an online, interactive lesson on geometric models. The author provides examples, exercises, and applets which include Buffon's problems, Bertrand's paradox, and random triangles. Additionally, the author provides links to external resources for students wanting to engage further in this topic. This is simply one lesson in a... http://www.math.uah.edu/stat/buffon/index.html
 Hypothesis Testing Created by Kyle Siegrist of the University of Alabama-Huntsville, this is an online, interactive lesson on hypothesis testing. The author provides examples, exercises, and applets about the concept. These include tests in the normal model, Bernoulli Model and two-sample normal model as well as likelihood ratio and goodness of fit tests. Additionally, the author provides a set of external... http://www.math.uah.edu/stat/hypothesis/index.html
 Random Samples Created by Kyle Siegrist of the University of Alabama-Huntsville, this is an online, interactive lesson on random samples. The author provides examples, exercises, and applets concerning many different topics. Some of these include: sample mean, law of large numbers, sample variance, partial sums, central limit theorem, special properties of normal samples, order statistics, and sample... http://www.math.uah.edu/stat/sample/index.html
 Probability Spaces Created by Kyle Siegrist of the University of Alabama-Huntsville, this is an online, interactive lesson on probability spaces. The resource provides examples, exercises, and applets that cover conditional probability, independence, and several modes of convergence that are appropriate for random variables. This section also covers probability space, the paradigm of a random experiment and its... http://www.math.uah.edu/stat/prob/index.html
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