Non-symbolic math

  • This pdf text file gives a short introduction to the methods of Bayesian inference. It gives a simple example that deals with jumping a paper frog. The topics listed in this document include: An example, comparison of frequentist and Bayesian methods, credible vs. confidence intervals, choice of prior and its effect on the posterior distribution.
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  • This site presents several photographs from real life that demonstrate natural statistical concepts. Each picture shows a statistical distribution made by some pattern occuring in everyday life. An explanation of each picture tells what distribution is being represented and how.
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  • This text article gives a relatively short description of the concept of p-values and statistical significance. This article aimed at health professionals frames the idea of statistical significance in the setting of a weight loss program. In addition to discussing p-values and comparing them with confidence intervals, the article touches on the ideas of practical significance and the fact that the significance of 0.05 is arbitrary.
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  • The Numbers Guy examines numbers in the news, business and politics. Some numbers are flat-out wrong or biased, while others are valid and help us make informed decisions. Carl Bialik tells the stories behind the stats, in daily updates on this blog and in his column published every other Friday in The Wall Street Journal.
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  • This NSF funded project provides worksheets and laboratories for introductory statistics. The overview page contains links to 9 worksheets that can be done without technology, which address the topics of obtaining data, summarizing data, probability, regression and correlation, sampling distributions, hypothesis testing and confidence intervals. The page also contains twelve laboratories that require the use of technology. Data sets are provided in Minitab format.
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  • A song describing how sample means will follow the normal curve regardless of how skewed the population histogram is, provided n is very large.

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  • You must never tell a thing. You must illustrate it. We learn through the eye and not the noggin. A quote on June 25, 1933 by American humorist, social commentator, and actor, Will Rogers (1879 - 1935) found in "The Will Rogers Book" Texian Press, 1972. The quote also appears in Statistically Speaking: A dictionary of quotations compiled by Carl Gaither and Alma Cavazos-Gaither.

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  • This tutorial on Friedman's Test includes its definition, assumptions, characteristics, and hypotheses. An example using output from the WINKS software is given, but those without the software can still use the tutorial. An exercise is given at the end that can be done with any statistical software package.
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  • This page discusses the differences in parametric and nonparametric tests and when to use then.
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  • This page discusses the proper procedures for multiple comparison tests and reasons behind them.
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