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  • Hiawatha Designs an Experiment is a poem by English statistician Sir Maurice George Kendall (1907 - 1983). The poem can be used in teaching about the trade-off between reliability and bias found in many inference problems and in designing experiments and interpreting the results of an ANOVA. The poem was originally published in "The American Statistician" December, 1959.

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  • Song about bootstrap resampling methods and their history. May be sung to the tune of Don McLean's 1971 song "American Pie." Lyrics by Giles Hooker (May, 2004). This song is part of the "Stanford Statistics Songbook" found at www.bscb.cornell.edu/~hooker/StanfordStatisticsSongbook.pdf Free to use for non-commercial educational purposes. Contact author to use in publications or for commercial purposes. Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.

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  • A cartoon to teach about the interpretation of confidence statements. The cartoon plays on the idea of what would happen if the same process was repeated over-and-over again. 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 presentation is a part of a series of lessons on the Analysis of Categorical Data.  This lecture overs the following: covariance patterns and generalized estimating equations (GEE). 

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  • This presentation is a part of a series of lessons on the Analysis of Categorical Data.  This lecture overs the following: conditional logistic regression, conditional likelihood for matched pairs, the non-central hypergeometric, the conditional maximum likelihood estimator (CMLE), conditional confidence interval for odds ratios, and McNemar's statistic.

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  • This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: maximum likelihood estimation for logistic regression, sample size requirements for approximate normality of the MLE’s, confidence intervals, likelihood ratio statistic, score test statistic, deviance, Hosmer-Lemeshow goodness-of-fit statistic, the Hosmer-Lemeshow statistic, parameter estimates, scaled/unscaled estimates, residuals, grouped binomials, and model building strategies.

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  • This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: generalized IxJ contingency tables, degrees of freedom, Fisher's exact test, and generalized odds ratio.

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  • This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: 2x2 contingency tables, fixing columns and rows, MLE, and previous topics within the context of contingency tables (variance, confidence intervals, standard error approximation, likelihood ratio, etc.).  

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  • This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following:  Wald test, score test, likelihood-ratio test, large sample confidence intervals, and the F distribution.

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  • Includes detailed PowerPoints for 20 lectures for topics including generalized linear models, logistic regression, and random effects models.

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