Resource Library

This site provides applets, lessons, and objectives for learning about conditional probability. The applet activity introduces multiple-outcomes events and computing probabilities.

This virtual applet simulates randomly drawing numbers from a box. You can choose which numbers you would like to choose from and the number of draws. The applet has the option to show theoretical probability and displays the results in histogram form.

This is a virtual applet, which models repeaded coin tossing by a random number generator. It allows you to change the number of tosses as well as runs and records your results.

This is a virtual spinner applet, which allows you to change spinner regions and the number of spins. It records the results and displays the data in a histogram.

An independent, nonpartisan resource on trends in American public opinion. Gives examples of recent polls, margins of error, questions asked, and sample sizes.

This lesson plan uses the Birthday Paradox to introduce basic concepts of probability. Students run a Monte Carlo simulation using the TI-83 graphing calculator to generate random dates, and then search for matching pairs. Students also perform a graphical analysis of the birthday-problem function. Key Words: Permutations; Explicit Function; Recursive Function; Modeling.

This page provides an example of pseudo random number generators (PRNG) creating spread spectrum broadcasts and signals for encryption and decryption of wireless transmissions.

Pseudo random number generators (PRNG) start with a seed value and will eventually repeat all the numbers they generate in exactly the same order. Putting in the same seed value will give precisely the same set of random numbers. On large scale Monte Carlo simulations (depends on generation of multiple random numbers), care has to be taken to make sure that the PRNG cycle is significantly longer than the quantity of random numbers needed or the pattern in the PRNG cycle can show up as an error producing pattern in the simulation results.

Using a parameter it's possible to represent a property of an entire population with a single number instead of millions of individual data points. There are a number of possible parameters to choose from such as the median, mode, or interquartile range. Each is calculated in a different manner and illuminates the data from a different point of view. The mean is one of the most useful and widely used and helps us understand populations. A population is simulated by generating 10,000 floating point random numbers between 0 and 10. Sample means are displayed in histograms and analyzed.

This page shows how elements of a systems can be eliminated as causes in problem troubleshooting. The principles of twenty questions are frequently used in the business world to conduct computerized searches of massive data bases. These are called a binary searches and are one of the fastest search methods available. To conduct binary searches, data must be sorted in order or alphabetized. The computer determines which half of the list contains the item. The half containing the item is divided in half again and the process repeated until the item is found or the list can no longer be divided. Problem solvers should avoid focusing on the cause and instead ask which elements of the system can be eliminated as causes.