Resource Library

A cartoon to be used in discussing the interpretation of a regression equation (for example interpreting the intercept when it is well beyond the range of the data). The cartoon is #1823 in the web comic Piled Higher and Deeper by Panamanian cartoonist Jorge Cham (1976- ): see www.phdcomics.com/comics/archive.php?comicid=1823. Free for use in classrooms and course websites with acknowledgement (i.e. "Piled Higher and Deeper" by Jorge Cham, www.phdcomics.com)

A cartoon to be used in discussing summary statistics (comparing means ± error bars). One aspect of part of the graph for discussion shows an error bar going below zero for a variable that should be positive. The cartoon is #1793 in the web comic Piled Higher and Deeper by Panamanian cartoonist Jorge Cham (1976- ): see www.phdcomics.com/comics/archive.php?comicid=1793. Free for use in classrooms and course websites with acknowledgement (i.e. "Piled Higher and Deeper" by Jorge Cham, www.phdcomics.com)

A cartoon to be used in discussing summary statistics that juxtaposes various interesting statistics. The cartoon is #1743 in the web comic Piled Higher and Deeper by Panamanian cartoonist Jorge Cham (1976- ): see www.phdcomics.com/comics/archive.php?comicid=1743. Free for use in classrooms and course websites with acknowledgement (i.e. "Piled Higher and Deeper" by Jorge Cham, www.phdcomics.com)

A quote to initiate a discussion of the fact that correlation does not imply a causal relationship (especially spurious correlations that happen by coincidence). The quote is by American novelist and poet Siri Hustvedt (1955 - ) from her 2011 novel The Summer Without Men.

This is an e-book tutorial for R. It is organized according to the topics usually taught in an Introductory Statistics course. Topics include: Qualitative Data; Quantitative Data; Numerical Measures; Probability Distributions; Interval Estimation; Hypothesis Testing; Type II Error; Inference about Two Populations; Goodness of Fit; Analysis of Variance; Non-parametric methods; Linear Regression; and Logistic Regression.

This site is an interactive, online tutorial for R. It asks the user to type in commands at an R prompt, which are then evaluated. Typing the right thing allows the user to continue on, typing the wrong thing yields an error. The user cannot skip the easier lessons. Lessons are: Using R; Vectors; Matrices; Summary Statistics; Factors; Data Frames; Real-World Data; and What’s Next.

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.

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 z-scores. The cartoon was used in the September 2016 CAUSE Cartoon Caption Contest. The winning caption was submitted by Amy Nowacki from Cleveland Clinic/Case Western Reserve University, while the drawing was created by John Landers using an idea from Dennis Pearl. A second winning caption "Even a crash course in model-fitting will need to consider distributions other than normal," was by Eugenie Jackson, a student at University of Wyoming, is well-suited for starting a conversation about the normality assumption in statistical models.(see "Cartoon: Pile-UP I") 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 cartoon to be used for discussing the value of data visualizations. The cartoon was used in the August 2016 CAUSE Cartoon Caption Contest. The winning caption was submitted by Barb Osyk from the University of Akron, while the drawing was created by John Landers using an idea from Dennis Pearl. Other honorable mentions that rose to the top of the judging included "I told you exploded pie charts are dangerous!" written by Aaron Profitt from God’s Bible School and College; "Liar liar, data on fire," written by Mickey Dunlap from University of Tennessee at Martin: and "I warned you about using hot deck imputation when you have so much missing data!" written by Elizabeth Stasny, from The Ohio State University. (to use this cartoon with an alternate caption simply download and replace the caption using a bolded comic sans font)