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  • Essentially, all models are wrong, but some are useful. This quote is generally attributed to George Box. It appears in "Empirical Model-Building and Response Surfaces" (Wiley 1987) p. 424 by George E.P. Box & Norman R. Draper.
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  • Song includes basic vocabulary from ANOVA. May be sung to "Nowhere Man" (John Lennon, Paul McCartney)
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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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  • This page calculates either sample size or power for a one sample binomial problem. Users choose between a one-sided and two-sided test and specify the null and alternative hypothesized proportions. The calculator also gives the critical value.

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  • This topic from an online textbook discusses standard error, confidence interval, and significance testing for a difference in percentages or proportions. It also covers paired alternatives and standard error of a total. Exercises and answers are also provided.
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  • This section of an online textbook discusses calculating the exact probability using observed sets of frequencies, constructing frequency tables, and computing p-values. Exercises and answers are provided.
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  • This site is part of an online textbook and discusses non-parametric tests. It explains the calculations, assumptions, and uses of the Wilcoxon ranked sum test. How to treat unpaired and paired samples is covered. Related exercises and answers are included.
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  • This section of an online textbook discusses the correlation coefficient and illustrated it visually through graphs. It explains calculations as well as how scatter plots can describe data. It covers significance tests for relationships, the Spearman rank correlation and the regression equation. Exercises and answers are included.
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  • Survival analysis is concerned with studying the time between entry to a study and a subsequent event. This site looks at the Kaplan-Meier survival curve, its method and how to calculate it. It provides exercises as well as answers.
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  • This article provides a data collection and analysis activity for illustrating simple linear regression and outlier analysis. The activity was designed to involve students in the process of data collection and to motivate studying the relationship between two quantitative variables. Students collect data on occurrences of letters in English text. These data are used to study the relationships between how often a letter occurs in English text, and: (1) the letter's Morse Code units and (2) the relative frequency of Scrabbleä‹¢ game tiles for the letter. Worksheets and answers to the activities are provided.
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