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  • A fun song about the average by American humorist and singer-songwriter Carla Ulbrich. The song was a finalist in the novelty category of the 2018 USA Songwriting Competition.  The song is also available at www.theacousticguitarproject.com/artist/carla-ulbrich/ and more about the singer can be found at her website at www.carlau.com. For classroom use, you might ask which lines in "Totally Average Woman" refer to ways in which the woman in the song is at the mean, and which refer to ways in which she is at the median. Permission from singer is for free use for teaching in classroom and course websites with attribution. Commercial users must contact the copyright holder.

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  • A song to be used in discussing the idea that the null hypothesis represents the model of no effect (with several common examples). The original music and lyrics were written in 2017 by Greg Crowther from Everett Community College. The song won an honorable mention in the 2017 A-mu-sing contest. In the current 2018 version the music is by Greg Crowther and the revised lyrics and vocals are by Greg Crowther and Larry Lesser from University of Texas at El Paso.

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  • A light bulb joke that can be used in discussing how the choice of model might affect the conclusions drawn.  The joke was submitted to AmStat News by Robert Weiss from UCLA and appeared on page 48 of the October, 2018 edition.

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  • Dr. Kuan-Man Xu from the NASA Langley Reserach Center writes, "A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. "

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  • This presentation was given by Aneta Siemiginowska at the 4th International X-ray Astronomy School (2005), held at the Harvard-Smithsonian Center for Astrophysics in Cambridge, MA. 

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  • Free statistical calculators online.  Our basic statistical calculators will help you in common tasks you might encounter and deal mostly with simple distributions. 

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  • This textbook from VassarStats introduces various statistical topics and contains interactive components. Topics include: Measurement Principles; Distributions; Correlation; Regression; Partial Correlation; Rank-Order Correlation; Statistical Significance; Sampling Distributions; Hypothsis Tests; Probability; Chi-Square; Fisher's Exact Test; t-Distribution; t-test; Mann-Whitney Test; Wilcoxon Signed-Rank Test; Analysis of Variance; F-Distribution; Kruskal-Wallis Test; Friedman Test; Analysis of Covariance. Several calculators and generators include: Binomial Probability; Normal Probability; Binomial Sampling Distribution; Chi-Square Sampling Distribution.

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  • Using the Fisher r-to-z transformation, this page will calculate a value of z that can be applied to assess the significance of the difference between two correlation coefficients, r_a and r_b, found in two independent samples. If r_a is greater than r_b, the resulting value of z will have a positive sign; if r_a is smaller than r_b, the sign of z will be negative.

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  • For a table of frequency data cross-classified according to two categorical variables, X and Y, each of which has two levels or subcategories, this page will calculate the Phi coefficient of association; perform a chi-square test of association, if the sample size is not too small; and perform the Fisher exact probability test, if the sample size is not too large. For intermediate values of n, the chi-square and Fisher tests will both be performed.

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  • This page will compute the t-test for either correlated or independent samples. One may copy and paste data in or type the data in individually.

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