Statistical Inference & Techniques

  • This site links to the article "Use of R as a Toolbox for Mathematical Statistics Exploration," to activities demonstrating the use of R programming language, and to the site where users can download R. Activities cover the following topics: calculation of a running variance, maximization of a non-linear function, resampling of a statistic, simple Bayesian modeling, sampling from multivariate normal, and estimation of power.
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  • This collection of applets simulate many different statistical concepts such as: distributions, correlation, hypothesis testing, regression, and ANOVA.
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  • Develops the idea of the transition matrix and what it can tell you.
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  • The user is be able to change the mean and the standard deviation using the sliders and see the density change graphically. The check buttons (68, 95, 99) will help one realize the appropriate percentages of the area under the curve. An example of thiis "68-95-99.7" rule follows.
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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 Java based applet gives students an opportunity to work through confidence interval problems for the mean. The material provides written word problems in which an individual must be able to correctly identify the given parts for a confidence interval calculation, and then be able to use this information to find the confidence interval. It gives step by step prompts to encourage students to choose the correct numbers and "cast of characters".
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  • This site provides a collection of applets and their descriptions. Some of the titles include the Monte Carlo Estimation of Pi, Can You Beat Randomness?, One-Dimensional Random Walk, Two-Dimensional Random Walk, The Anthill and Molecular Motion, Diffusion Limited Aggregation, The Self-Avoiding Walk, Fractal Coastlines, and Forest Fires and Percolation.
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  • This is the description and instructions for the Monte Carlo Estimation of Pi applet. It is a simulation of throwing darts at a figure of a circle inscribed in a square. It shows the relationship between the geometry of the figure and the statistical outcome of throwing the darts.
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  • This is the description and instructions for the Can You Beat Randomness?- The Lottery Game applet. It is a simulation of flipping coins. Students are asked to make conjectures about randomness and how certain strategies affect randomness. It strives to show the "growth of order out of randomness."
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  • This is the description and instructions for the One-Dimensional Random Walk applet. This Applet relates random coin-flipping to random motion. It strives to show that randomness (coin-flipping) leads to some sort of predictable outcome (the bell-shaped curve).
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