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 Law of Large Numbers Created by Charles M. Grinstead and J. Laurie Snell of Dartmouth College, this website is part of an online statistics textbook. Topics include: (1) Law of Large Numbers for Discrete Random Variables, (2) Chebyshev Inequality, (3) Law of Averages, (4) Law of Large Numbers for Continuous Random Variables, (5) Monte Carlo Method. There are several examples and exercises that accompany the... http://www.dartmouth.edu/~chance/teaching_aids/books_article...
 Monte Carlo Simulation: The Power of the Chi-Square In the first simulation, random samples of size n are drawn from the population one sample at a time. With df=3, the critical value of chi-square for significance at or beyond the 0.05 level is 7.815; hence, any calculated value of chi-square equal to or greater than 7.815 is recorded as "significant," while any value smaller than that is noted as "non-significant." The second simulation does... http://faculty.vassar.edu/lowry/chi_beta.html
 Statistical Reference Datasets: Archives The datasets on this page are classified by analysis techniqueand by level of difficulty (lower, average, higher). They were originally intended to test statistical software. The sets cover these topics: ANOVA, linear regression, Markov Chain Monte Carlo, nonlinear regression, and univariate summary statistics. This is a nice collection as it not only contains raw data but also helps explain the... http://www.itl.nist.gov/div898/strd/general/dataarchive.html
 Bacteria Allocation Using Monte Carlo This applet, created by David Hill and Lila Roberts, uses the Monte Carlo technique to simulate a count of bacteria that are present as a result of a certain sampling process. This simulation could be modified to perform other experiments. This experiment is geared towards high school calculus students or probability courses for mathematics majors in college. Students must possess a basic... http://www.mathdemos.org/mathdemos/MCBact/MCBact.html
 Monte Carlo Estimation for Pi 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. http://polymer.bu.edu/java/java/montepi/MontePi.html
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