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Undergraduate students

  • 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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  • 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 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 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.
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  • 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.
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  • The Comprehensive Epidemiologic Data Resource is a collection of data sets. It includes definitions of each variable in the data set. It requires a login to retrieve the data sets. Registering involves giving your name and address and the name of the study and a detailed description of the intended use of the data.
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  • This complete lesson plan, which includes assessments, is based upon a data set partially discussed in the article "Female Hurricanes are Deadlier than Male Hurricanes." The data set contains archival data on actual fatalities caused by hurricanes in the United States between 1950 and 2012. Students analyze and explore this hurricane data in order to formulate a question, design and implement a plan to collect data, analyze the data by measures and graphs, and interpret the results in the context of the original question.
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  • A reference for analyzing large, complex data sets. Helpful for various levels of students.

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  • This webpage provides an active learning lesson for linear regression. Resources include an in-class student activity sheet for two different levels of classes (Algebra I and Junior), a PowerPoint showing faces of famous people, and sheet with updated (to the end of current year) actual ages of the celebrities.
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