# Elementary Probability

• ### Buffon's Needle JAVA Sourcecode

This is a "Building Block" for the Buffon Needle problem. The source code and compile code are included as well as separate files for each. Users able to test the applet to determine if it meets their needs.

• ### The Poisson Process

This online, interactive lesson on the Poisson process provides examples, exercises, and applets. Specific topics include the exponential distribution, gamma distribution, Poisson distribution, splitting a Poisson process, analogy with Bernoulli trials, and higher dimensional Poisson processes.
• ### Quote: Churchill on Statistics

The only statistics you can trust are those you falsified yourself is a quote attributed to former British Prime Minister Sir Winston Churchill (1874 - 1965). However scholars at the Churchill Centre (www.winstonchurchill.org) can not find this quote in any of Winston Churchill's books, articles, or speeches.
• ### ** Sampling from a Real Estate Database

This material is a detailed exercise for students in introductory statistics. Students are asked to collect a random sample of data from a real estate website; conduct descriptive statistics (including confidence intervals); and write a report summarizing their dataset. The primary learning goals are to teach students 1) how to obtain a random sample; 2) how to interpret confidence intervals; 3) how to simulate and interpret a sampling distribution; and 4) how to communicate descriptive statistics.
• ### Analysis Tool: Statistics Online Computational Resources (SOCR)

This applets on this site include: interactive graphs of many distribution models; a collection of computer generated games; a collection of data modeling aids including curve fitting, wavelets, matrix manipulations, etc.; p-values, quantiles & tail-probabilities calculations; virtual online probability experiments and demonstrations; and a large collection of statistical techniques for online data analysis, visualization, and integration.

• ### The Marble Game

The Marble Game is a "concept model" demonstrating how a binomial distribution evolves from the occurence of a large number of dichotomous events. The more events (marble bounces) that occur, the smoother the distribution becomes.
• ### Impact!

This is an exercise in interpreting data that is generated by a phenomenon that causes the data to become biased. You are presented with the end product of this series of events. The craters occur in size classes that are color-coded. After generating the series of impacts, it becomes your assigned task to figure out how many impact craters correspond to each of the size class categories.
• ### Probability Spaces

This online, interactive lesson on probability spaces 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 mathematical model as well as sample spaces, events, random variables, and probability measures.

• ### Teaching Bayesian Reasoning in Less Than Two Hours

This journal article describes a set of experiments in which different methods of teaching Bayes' Theorem were compared to each other. The frequency representation of the rule was found to be easier to learn than the probability representation.
• ### Sufficient Statistics

This page introduces the definition of sufficient statistics and gives two examples of the use of factorization to prove sufficiency.