Probability

  • Luck is probability taken personally. It is the excitement of bad math. A quote of comedian and illusionist Penn F. Jillette (1955 - )
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  • A knowledge of statistics is like a knowledge of foreign languages or of algebra; it may prove of use at any time under any circumstances. Quote from "Elements of Statistics" by English statistician, economist and early proponent of using statistics in the social sciences, Sir Arthur Lyon Bowley (1869 - 1957).
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  • Life is a school of probability. A quote attributed to English journalist and longtime editor of "The Economist" newspaper, Walter Bagehot (1826 - 1877). The quote is found in "The World of Mathematics", J.R. Newman (ed.); Simon and Schuster, 1956 p. 1360.
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  • 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.
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  • This applet was designed to illustrate the impact on simple linear regression output caused by adding a new data point. The applet simulates data and provides a graphical display of the data points and fitted regression line as well as the updated regression line after the addition of a data point.
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  • This page calculates either estimates of sample size or power for differences in proportions. The program allows for unequal sample size allocation between the two groups.

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  • This applet displays various distributions and allows the user to experiment with the parameters to see the effects on the curve.

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  • Submitting your spotlight presentation from USCOTS 2005 to CAUSEweb is an easy process, and you are in a prime position to submit your work! What better way to have your work showcased than in a peer-reviewed repository of contributions to statistics education? This Webinar from January 2006 provided an opportunity to talk about how to prepare your USCOTS spotlight for submission to CAUSEweb and to discuss the benefits of submission.

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  • A cartoon to use at the end of a class period when the instructor was rushed to finish. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.
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  • This Flash based applet simulates data from a case study of treatments for tumor growth in mice. This simulation allows the user to place mice into a control and treatment groups. The simulation then compares the difference in the groups based on this haphazard selection to those of a truly random assignment (the user may also create multiple random assignments and examine the sampling distribution of key statistics). The applet may be used to illustrate three points about random assignment in experiments: 1) how it helps to eliminate bias when compared with a haphazard assignment process, 2) how it leads to a consistent pattern of results when repeated, and 3) how it makes the question of statistical significance interesting since differences between groups are either from treatment or by the luck of the draw. In this webinar, the activity is demonstrated along with a discussion of goals, context, background materials, class handouts, and assessments. Key Note for Instructors: The data are drawn from a real experiment with an effective treatment but where the response is correlated with animal age and size (so tumor size will tend to be smaller in the treatment group when measured at the end of a randomized experiment but animal age and size should not be). Typically people choosing haphazardly will tend to pick larger/older animals for the treatment group and thus create a bias against the treatment.
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