Data Collection

  • Many data sets useful for modeling bivariate relationships. The data sets are formatted for use in Fathom, but text versions are also available.
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  • 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.
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  • 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.
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  • 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.
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  • 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.
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  • 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.
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  • Big data analysis is explained in this online course that introduces the user to the tools Hadoop and Mapreduce. These tools allow for the parallel computing necessary to analyze large amounts of data.
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  • 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.
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  • A cartoon to be used for discussing the importance of efficiency in sampling. The cartoon was used in the April 2017 CAUSE Cartoon Caption Contest. The winning caption was submitted by Mickey Dunlap from University of Georgia. The drawing was created by British cartoonist John Landers based on an idea from Dennis Pearl of Penn State University. Three honorable mentions that rose to the top of the judging in the April competition included “Better to ask for help BEFORE you're drowning in data!,” written by Larry Lesser from University of Texas at El Paso; “I guess I should have asked for more details before signing up for this "Streaming Data" workshop,” written by Chris Lacke from Rowan University; and “On reflection, random sampling WITH replacement might not have been appropriate in this scenario,” written by Aaron Profitt from God’s Bible School and College.
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  • A cartoon to be used for discussing the value of stratification in reducing the variability of population estimates (and the difficulty in doing so when the population weights are unknown).. The cartoon was used in the May 2017 CAUSE Cartoon Caption Contest. The winning caption was submitted by Jim Alloway of EMSQ Associates. The drawing was created by British cartoonist John Landers based on an idea from Dennis Pearl of Penn State University. Two honorable mentions that rose to the top of the judging in the May competition may be found at https://www.causeweb.org/cause/resources/fun/cartoons/product-testing-ii written by Larry Lesser from University of Texas at El Paso and at https://www.causeweb.org/cause/resources/fun/cartoons/product-testing-iii written by John Bailer from Miami University.
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