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Categorical versus Quantitative

  • Which is more robust against outliers: mean or median?  This app demonstrates the (in)stability of these descriptive statistics as the value of an outlier and the number of data points change.

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  • The goal of this text is to provide a broad set of topics and methods that will give students a solid foundation in understanding how to make decisions with data. This text presents workbook-style, project-based material that emphasizes real world applications and conceptual understanding. Each chapter contains:

    • An introductory case study focusing on a particular statistical method in order to encourage students to experience data analysis as it is actually practiced.
    • guided research project that walks students through the entire process of data analysis, reinforcing statistical thinking and conceptual understanding.
    • Optional extended activities that provide more in-depth coverage in diverse contexts and theoretical backgrounds. These sections are particularly useful for more advanced courses that discuss the material in more detail. Some Advanced Lab sections that require a stronger background in mathematics are clearly marked throughout the text.
    • Data sets from multiple disciplines and software instructions for Minitab and R.

    The text is highly adaptable in that the various chapters/parts can be taken out of order or even skipped to customize the course to your audience. Depending on the level of in-class active learning, group work, and discussion that you prefer in your course, some of this work might occur during class time and some outside of class. 

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  • CODAP provides an easy-to-use web-based data analysis platform, geared toward middle and high school students, and aimed at teachers and curriculum developers. CODAP can be incorporated across the curriculum to help students summarize, visualize and interpret data, advancing their skills to use data as evidence to support a claim.

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  • This site did a lot of data visualization on many hot button topics. They provide the raw data that they used to create their graphs at this page. These data sets are kept in Google Doc spreadsheets.
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  • The Census Bureau has made many data visualizations of the data it collects. It is a good collections of maps, treemaps, an age/sex pyramid, and of course more familiar graphs, like bar graphs.
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  • 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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  • 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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  • This collection of datasets was compiled by the Biostatistics Department at Vanderbilt University. They come in R, S, Excel, and ASCII formats. Each also has a description in html format.
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  • This textbook from VassarStats introduces various statistical topics and contains interactive components. Topics include: Measurement Principles; Distributions; Correlation; Regression; Partial Correlation; Rank-Order Correlation; Statistical Significance; Sampling Distributions; Hypothsis Tests; Probability; Chi-Square; Fisher's Exact Test; t-Distribution; t-test; Mann-Whitney Test; Wilcoxon Signed-Rank Test; Analysis of Variance; F-Distribution; Kruskal-Wallis Test; Friedman Test; Analysis of Covariance. Several calculators and generators include: Binomial Probability; Normal Probability; Binomial Sampling Distribution; Chi-Square Sampling Distribution.
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