Resource Library

The individual source of the statistics may easily be the weakest link. Harold Cox tells a story of his life as a young man in India. He quoted some statistics to a Judge, an Englishman, and a very good fellow. His friend said, Cox, when you are a bit older, you will not quote Indian statistics with that assurance. The Government are very keen on amassing statistics ... they collect them, add them, raise them to the nth power, take the cube root and prepare wonderful diagrams. But what you must never forget is that every one of these figures comes in the first place from the `chowty dar` [village watchman], who just puts down what he damn pleases." Quoted from "Some Economic Factors in Modern Life" (King and Son, 1929; p. 258) by Sir Josiah Charles Stamp (1880 - 1941), British economist, statistician, director of the Bank of England and president of the Royal Statistical Society.

I feel like a fugitive from the law of averages. A quote of soldier and U.S. cartoonist William H. Mauldin (1921 - 2003) from a cartoon caption in the first published collection of his work, "Up Front" (H. Holt and Co., 1945)

While nothing is more uncertain than the duration of a single life, nothing is more certain than the average duration of a thousand lives. A quote of American actuary and abolitionist Elizur Wright (1804 - 1885).

It is a good morning exercise for a research scientist to discard a pet hypothesis every day before breakfast. It keeps him young. A quote of Austrian animal behaviorist Konrad Lorenz (1903 - 1989) in "On Aggression", (English translation: 1966, Harvest books) p. 12. Quote also found in "Statistically Speaking - a Dictionary of Quotations" compiled by Carl Gaither and Alma Cavazos-Gaither p. 119.

During this simulation activity, students generate sampling distributions of the sample mean for n = 5 and n = 50 with Fathom 2 and use these distributions to confirm the Central Limit Theorem. Students sample from a large population of randomly selected pennies. Given that the variable of interest is the age of the pennies, which has a geometric distribution, this is a particularly convincing demonstration of the Central Limit Theorem in action. This activity includes detailed instructions on how to use Fathom to generate sampling distributions. The author will provide the Fathom data file upon request.

This FLASH based applet illustrates the sampling distribution of the mean. This applet allows the user to pick a population from over 2000 pre-defined populations. The user can then choose size of the random sample to select. The applet can produce random samples in one, 10, 100, or 1000 at a time. The resulting means are illustrated on a histogram. The histogram has an outline of the normal distribution and vertical lines at 1, 2, and 3 standard deviations. The applet can be viewed at the original site or downloaded to the instructors machine.

This program allows the student to explore the nature of sampling distributions of sample means and sample proportions. The software provides separate windows for building population distributions, drawing and viewing random samples from the population, exploring the behavior of sampling distributions of sample means, and exploring the behavior of confidence intervals.

This activity uses a computer program to explore probability concepts such as sample space, independent events, law of large numbers, and reliability. An outline of the activity and the computer program are provided.

This applet simulates randomly assigning newborn babies to families and measures the number of matches, or instances when a baby is assigned to its real family. The applet keeps track of each trial and records the information in a histogram. The idea is to teach theoretical values associated with random sampling. The relation website is a worksheet activity to accompany the applet.

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.