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  • This resource defines and explains the median using an example on employee salaries.
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  • This resource defines and explains percent changes using an example on city murder rates.
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  • This resource defines and explains per capita rates using an example on city murder rates.
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  • This resource explains margin of error using an example on presidential popularity polls.
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  • This resource gives 3 questions readers should ask when presented with data and why to ask them: Where did the data come from? Have the data been peer-reviewed? How were the data collected? This page also describes why readers should: be skeptical when dealing with comparisons, and be aware of numbers taken out of context.

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  • This resource discusses sample sizes and how they are chosen.
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  • This resource explains the t-distribution and hypothesis testing (informally) using an example on laptop quality.
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  • This day may possibly be my last: but the laws of probability, so true in general, so fallacious in particular, still allow about fifteen years. A quote of English historian Edward Gibbon (1737 - 1794). The quote was written in 1787 and was published after his death in "Miscellaneous works of Edward Gibbon, with memoirs of his life and writings composed by himself" edited by Lord John Seffield, 1796
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  • This article, in a series, describes a game, which tests opposing strategies through aspects of experiemental design.
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  • The following exercise can illustrate the problem of bias in estimators to students in statistics courses. In some advanced courses an alternative estimator may be presented and properties of this estimator may be investigated via Monte Carlo studies.
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