Resource Library

This tutorial on SQL teaches the most used commands. There is a short explanation, then the user is asked a simple question. If the typed answer is correct, the user continues to the next lesson.

A cartoon to aid in the discussion of the importance of replication. The cartoon was created in 2017 by Lyla El-Fayomi, a student at the University of Toronto at Mississauga and won an honorable mention in the cartoon category of the 2017 A-mu-sing competition.

A cartoon to aid in the discussion of the difference between descriptive and inferential statistics. The cartoon was created by Greg Crowther from Everett Community College and took second place in the cartoon category of the 2017 A-mu-sing competition.

A cartoon to aid in the discussion of volunteer sampling and response bias in surveys. The cartoon was created in 2017 by Sabrina Cappella, a student at the University of Toronto at Mississauga and took the grand prize in the 2017 A-mu-sing competition.

This collection of datasets from Dr. John Rasp's Statistics Webpage is for his STAT 460 (Experimental Design & Advanced Data Analysis), STAT 301 (Business Statistics), STAT 201 (Intro to Business Statistics) classes. This also provides links for statistical web pages, resources for statistical studies, Homework and lecture reviews.

This is a collection of data sets that were part of R packages. The data set page includes information on which package the data set comes from, the name of the data set, and the number of rows and columns included. Each set is given in .csv form with a documentation file also.

This site presents 19 videos of statisticians summarizing a project that they did. Each video is accompanied by a dataset so that viewers can try to recreate the statistics in the video. Video runtimes vary from about 8 minutes to as many as 35 minutes.

Many data sets useful for modeling bivariate relationships. The data sets are formatted for use in Fathom, but text versions are also available.

Data sets were submitted by the authors of articles in JSE. Each data set is presented along with a link to the article that references the data.

This collection of data can be used for many useful statistical analyses. Data and description are in a separate file and useful for SAS data analysis too. Data are categorized by analysis type, hence easy to pic relevant data sets accordingly. The data can be used for many analysis such as, Categorical data analysis, Polynomial Linear, Nonlinear, Logistic, Poisson, Negative Binomial Regression analysis, Response Surface Regression, Binary Response Regression, Time Series Data,1-Way ANOVA/ Independent Samples t-test, Multi-Factor ANOVA, and many other data analysis.