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Algebra level symbolic math

  • This online software allows you to load data and make professional-looking graphs with it. Graph types are basic (scatterplot, line plot, bar charts, etc.), statistical (histograms, box plots), scientific (error bars, heat map, contour), 3D charts, and financial (e.g. time series). Other graphs are available with the paid pro version. Log in is required, which allows you to upload data and save it for next use.

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  • This online application allows the user to import data from online resources such as Facebook, Google Analytics, GitHub, as well as spreadsheets on their own computers. They can then drag-and-drop variables to make graphs automatically. The basic version is free, but you can upgrade to a paid version which allows combining data across services and, if the data come from an online resource, the user has the choice to have Data Hub keep the graphs updated as the data changes.
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  • A game to aid in teaching experimental design and significance testing (especially one sample, two sample, and matched pair situations). Tangrams are puzzles in which a person is expected to place geometrically shaped pieces into a particular design. The on-line Tangram Game provides students the opportunity to design many versions of the original game in order to test which variables have the largest effect on game completion time. A full set of student and instructor materials are available and were created by Kevin Comiskey (West Point), Rod Sturdivant (Ohio State University) and Shonda Kuiper (Grinnell College) as part of the Stat2Labs collection.

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  • This software makes it easier to use the R language. It includes a code debugger, editing, and visualization tools.

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  • This is a web application framework for R, in which you can write and publish web apps without knowing HTML, Java, etc. You create two .R files: one that controls the user interface, and one that controls what the app does. The site contains examples of Shiny apps, a tutorial on how to get started, and information on how to have your apps hosted, if you don't have a server.

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  • 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.
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  • This online booklet, Start Teaching with R, by Randall Pruim, Nicholas J. Horton, and Daniel T. Kaplan comes out of the Mosaic project. It describes how to get started teaching Statistics using R, and gives teaching tips for many ideas in the course, using R commands.

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  • 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.
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  • 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.
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  • This site has the data and shows the code you would use to replicate the examples in Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence, by Judith D. Singer and John B. Willett. It has code in SAS, R, Stata, SPSS, HLM, MLwiN, and Mplus.
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