This is my take on the ubiquitous M&Ms counting activity. Each student records the color proportions in a fun-size bag of M&Ms. We pool the class data and run a Chi-Square goodness-of-fit test to determine whether or not the color proportions match those claimed on the manufacturer's website. We consistently find that the proportions do not match. The blue M&Ms, in particular, are underrepresented. This activity also includes a review of the 1-proportion z confidence interval.
Song about the chi-square goodness-of-fit test. May be sung to the tune of James Rado, Gerome Ragni, and Gai MacDermot's 1969 song "Aquarius" from the musical "Hair." Lyrics by Lawrence Mark Lesser. Musical accompaniment realization are by Joshua Lintz and vocals are by Mariana Sandoval from University of Texas at El Paso.
Probability is a 2 minute 14 second video that can be used in discussing the probability of rare events (e.g. how many consecutive times must a coin land heads before you question whether it is a fair coin?). The video was written, shot, and edited by Sam Rapien in 2007. The music is by Brett Musil and Sam Rapien and the single cast member is Jon Anderson. Mr. Rapien made this video while a graduate student in the Department of Art and Art History at the University of Nebraska, Lincoln.
Outliers is a triangular shaped poem written in 2008 by Jacqueline Shaffer (1980 - ) of California State University, East Bay. The poem focuses on the issue that outliers should not be removed from a data set without a reason.
Song about the need to show a significant result in order to have a manuscript published. May be sung to the tune of Robert Feldman, Gerald Goldstein and Richard Gottehrer's 1963 song "My Boyfriend's Back," popularized by The Angels. Lyrics by Marc Coram and Matthew Finkelman (December, 2003). 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.
This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: iterative solutions to non-linear equations, score equations for exponential class variables, Newton-Raphson vs. Fisher’s Scoring, Logistic Regression for an R × 2 tables, saturated model, odds ratios when rows are not ordinal, goodness of fit, likelihood ratio statistic for nested models, and residuals.
This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: linear association, correlation coefficient, ridits/modified ridits, nonparametric methods, Cochran-Armitage Trend test,
This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: multinomial distribution, LaGrange multipliers, Exact Multinomial Test (EMT), the Pearson statistic, and goodness of fit.
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.
This is a graduate level introduction to statistics including topics such as probabilty/sampling distributions, confidence intervals, hypothesis testing, ANOVA, and regression. Perfect for students and teachers wanting to learn/acquire materials for this topic.