Resource Library

This site shows the code you would use to replicate the examples in Applied Survival Analysis, by Hosmer and Lemeshow. It has code in Stata, R, and SAS.

This online booklet comes out of the Mosaic project. It is a guide aimed at students in an introductory statistics class. After a chapter on getting started, the chapters are grouped around what kind of variable is being analyzed. One quantitative variable; one categorical variable; two quantitative variables; two categorical variables; quantitative response, categorical predictor; categorical response, quantitative predictor; and survival time outcomes.

This is a youtube video by Jeremy Balka that was published in May 2013. The video presents a discussion of the assumptions when using the t distribution in constructing a confidence interval for the population mean. By considering various population distributions, the effect of different violations of the normality assumption is investigated through simulation.

These slides from the 2014 ICOTS workshop describe a minimal set of R commands for Introductory Statistics. Also, it describes the best way to teach them to students. There are 61 slides that start with plotting, move through modeling, and finish with randomization.

A cartoon to be used for discussing the F test in ANOVA and for discussing general student anxiety about statistics. The cartoon was used in the December 2016 CAUSE Cartoon Caption Contest. The winning caption was submitted by Larry Lesser at The University of Texas at El Paso, while the drawing was created by John Landers using an idea from Dennis Pearl. A second winning caption "Mark was pleased to note that he was a significant outlier. Little did he know it was a two-sided test..." written by Robert Garrett, a student at Miami University is well-suited to stimulate a discussion of statistical hypothesis testing and the effect of outliers (see "Cartoon: The Exam I")

A cartoon to be used for discussing statistical hypothesis testing and the effect of outliers. The cartoon was used in the December 2016 CAUSE Cartoon Caption Contest. The winning caption was submitted by Robert Garrett, a student at Miami University, while the drawing was created by John Landers using an idea from Dennis Pearl. A second winning caption "The sadistic ANOVA problem made most students feel headed for an F test," written by Larry Lesser from University of Texas at El Paso is well-suited to stimulate a discussion of the F test in ANOVA and about general student anxiety about statistics (see "Cartoon: The Exam II")

A cartoon to be used for discussing the nature of conclusions for a significance test. The cartoon was used in the November 2016 CAUSE Cartoon Caption Contest. The winning caption was submitted by Andrea Boito from Penn State University, Altoona, while the drawing was created by John Landers using an idea from Dennis Pearl. Two honorable mentions that rose to the top of the judging in the November competition included a repackaging of the classic refrain "If you torture data enough it will confess," written by Caleb Ohrn, a student at Akron University and "Did you check to see if the conditions were met? Ignore them at your own peril!" written by an anonymous author.

A cartoon to be used for discussing the normality assumption in statistical models. The cartoon was used in the September 2016 CAUSE Cartoon Caption Contest. The winning caption was submitted by Eugenie Jackson, a student at University of Wyoming while the drawing was created by John Landers using an idea from Dennis Pearl. A second winning caption was by Amy Nowacki from Cleveland Clinic/Case Western Reserve University whose entry “The dangers of driving more than 3 standard deviations below the speed limit,” would be useful in a classroom discussion of z-scores (see "Cartoon: Pile-UP II") Honorable mentions that rose to the top of the judging in the September caption contest included “Big pile-up at percentile marker -1.96 on the bell-curve. You might want to take the chi-square curve to avoid these negative values,” written by Mickey Dunlap from University of Tennessee at Martin; “Call the nonparametric team! This is not normal!” written by Semra Kilic-Bahi of Colby-Sawyer College; “I assumed the driving conditions today would be normal!” written by John Vogt of Newman University; and “CAUTION: Z- values seem smaller than they appear. Slow down & watch for stopped traffic reading these values,” written by Kevin Schirra, a student at University of Akron.

A "haiku" poem written by Larry Lesser from The University of Texas at El Paso. The poem is a playful vehicle to help introduce the chi-square test for contingency tables.

"Black Swan" is a poem by Scottish poet Eveline Pye from Glasgow Caledonin University. The poem was originally published in the September 2011 issue of the bimonthly magazine Significance, in an article about Eveline Pye's statistical poetry. "Black Swan" might be used in course discussions of the idea that just because an event has not been observed to date does not mean that it is impossible (see Taleb's Black Swan Theory).