Resource Library

A cartoon to be used in discussing density functions, scatterplots, and correlation. The plot is humorously labeled a density function – but is more readily interpreted as a scatterplot (in class discussions try to pin down how to interpret x and y). As a scatterplot, it shows a fairly clear (non-linear) association between x and y but would have a correlation of essentially zero. The cartoon is #1438 in the web comic Piled Higher and Deeper by Panamanian cartoonist Jorge Cham (1976- ): see www.phdcomics.com/comics/archive.php?comicid=1438. 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 correlation, spurious versus causal relationships, and the meaning of residuals (humorously depicting a relationship between residual over historical enrollment levels in grad school and residual levels in the unemployment rate). The cartoon is #1078 in the web comic Piled Higher and Deeper by Panamanian cartoonist Jorge Cham (1976- ): see www.phdcomics.com/comics/archive.php?comicid=1078. 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 the least squares property of the regression line and the lexical ambiguity in the use of the word regression. The cartoon is #1921 in the web comic Piled Higher and Deeper by Panamanian cartoonist Jorge Cham (1976- ): see www.phdcomics.com/comics/archive.php?comicid=1921. 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 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.