 CHANCE  J. Laurie Snell, Mathematics Dept., Dartmouth College
Materials designed to help teach a "Chance" course or a more standard introductory probability or statistics course. A Chance course is a case study quantitative literacy course designed to make students more informed and critical readers of current news items that use probability and statistics, as reported in daily newspapers. This site contains: Chance News, a monthly newsletter with abstracts of articles from current newspapers and journals, and suggestions for discussion questions for class use, with an archive; video lectures and audio discussions of Chance topics; syllabi of previous Chance courses and articles that have been written about them; a Teacher's Guide and other materials useful for teaching a Chance course; and links to related Internet sources for teaching a probability or statistics course. The Chance team of developers includes: J. Laurie Snell and Peter Doyle of Dartmouth College, Joan Garfield of the University of Minnesota, Tom Moore of Grinnell College, Bill Peterson of Middlebury College, and Ngambal Shah of Spelman College.
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 Gallery of Data Visualization  Michael Friendly, York University
Examples of the best and worst of statistical graphics, from what is arguably the best statistical graphic ever drawn, to the current recordholder for the worst.
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 HyperStat Online  David M. Lane; Rice Virtual Lab in Statistics
An introductorylevel hypertext statistics book. In addition to search capabilities, a glossary, analysis tools, and instructional demos, the book provides chapters on: describing univariate and bivariate data; introduction to probability; normal and sampling distributions; point estimation; confidence intervals; the logic of hypothesis testing; testing hypotheses with standard errors; power; introduction to betweensubjects ANOVA; factorial betweensubjects ANOVA; withinsubjects ANOVA; prediction; chi square; distributionfree tests; and measuring effect size.
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 K12 Practitioners' Circle  National Center for Education Statistics (NCES)
New content: a site designed to make the search for NCES and selected U.S. Department of Education K12 resources fast, easy, and productive. NCES offers a wealth of information for K12 practitioners, which this site attempts to put within easy reach. Although practitioners comprise more than administrators, teachers, policymakers, librarians, and parents, the site is targeted to these particular audiences.
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 Probability and Statistics  Math Forum
Links to some of the best Internet resources for probability and statistics: classroom materials, software, Internet projects, and public forums for discussion.
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 Probability and Statistics (MathPages)  Kevin Brown
More than 40 "informal notes" by Kevin Brown on probability and statistics: evaluating probabilities of Boolean events, area under the bell curve, N items distributed in M bins, dice rolling a given sum, a better lottery, meetings and birthdays, on random chords, and many more.
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 Statistics  Dave Rusin; The Mathematical Atlas
A short article designed to provide an introduction to statistics: the science of obtaining, synthesizing, predicting, and drawing inferences from data. Elementary calculations of mean and standard variation suffice to summarize a large, finite,
normallydistributed dataset; the field of Statistics exists since data are not usually so nicely given. If we do not know all the elements of the dataset, we must discuss sampling and experimental design; if the data are not normal we must use other parameters to summarize them, or resort to nonparametric methods; if multiple data are involved, we study the measures of interaction among the variables. Other topics include the study of timedependent data, and the foundations necessary to avoid ambiguity or paradox. Computational methods (e.g. for curvefitting) are of particular importance in applications to the sciences and engineering as well as financial and actuarial work. History; applications and related fields and subfields; textbooks, reference works, and tutorials; software and tables; other web sites with this focus.
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 Statistics Every Writer Should Know  Robert Niles; Niles Online
Numbers can't talk, but they can tell you as much as human sources can. Here, described in plain English, are some basic concepts in statistics that every writer and reader should know. For beginners: Mean, Median, Percent; the next step: Per capita and Rates, Standard Deviation and Normal Distribution, Margin of Error and Confidence Interval, Data Analysis; Frequently Asked Questions: Sample Sizes; Ask for Help: The Stats Board. With a link to Finding Data on the Internet, a journalist's guide.
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 Statistics (WWW Virtual Library)  Dept. of Statistics, University of Florida
Web information systems relating to Statistics. Data sources; job announcements; links to departments, divisions, and schools of statistics (Australia, Brazil, Canada, Europe, Israel, Mexico, New Zealand, United Kingdom, United States); statistical research groups, institutes, and associations; statistical services; statistical archives and resources; software vendors and FAQs; journals; mailing lists and newsgroups; and related fields.
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 StatLib  Dept. of Statistics, Carnegie Mellon University (CMU)
A system for distributing statistical software, datasets, and information by electronic mail, FTP, gopher, and WWW. Quick summary of contents, longer annotations.
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 StatSoft Electronic Textbook  StatSoft, Inc.
"The Encyclopedia Britannica for nonmathematical statistics users." This searchable virtual textbook includes hundreds of illustrations and offers quick, easy and free unlimited access to training in the understanding and application of statistics. It covers a wide variety of applications: laboratory research (biomedical, agricultural, etc.), business statistics and forecasting, social science statistics and survey research, data mining, engineering and quality control applications, and many others. Beginning with an overview of relevant elementary/pivotal concepts, it continues with indepth explorations of specific areas of statistics, organized by modules representing classes of analytic techniques. Includes a glossary and references. Developed at the StatSoft Research & Development department
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 SURFSTAT australia  Keith Dear; National Centre for Epidemiology and Population Health, The Australian National University
An online text in introductory Statistics from the University of Newcastle. Contents: Summarizing and Presenting Data (Types of Variate; Presenting Discrete and Continuous Data; Charactistics of a Distribution; Measures of Central Tendency and Variability; Normal Distributions; Presenting Data for Two Continuous Measurements; Exploring Data in Tables); Producing Data (Principles of Study Design); Variation and Probability (Independence and Tree Models for Calculating Probabilities; Conditional Probability; Bayes' Theorem; Random Variables; Discrete Distributions; Expected Value and Variance of a Random Variable; Continuous Random Variables; Normal Distribution; Normal Approximation to the Binomial Distribution); Statistical Inference (Populations, Samples, Estimates and Repeated Sampling; Point Estimation and Interval Estimation; Results from Probability Theory; One Continuous Variable; Comparing Means of Two Continuous Variables; Inference for Count Data; More on Correlation and Regression; Summary); Statistical Inference  Control Charts. Includes a Glossary of terms and a hotlist for Java applets.
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