Non-symbolic math

  • This site lists a set of case studies that cover regression topics, random number calculations of pi, as well as limit theorems. On the individual case study pages are the descriptions and/or instructions.
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  • This applet shows balls falling through a grid of posts to show the central limit theorem in action.
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  • This part of the NIST Engineering Statistics handbook describes different graphs and plots used in Exploratory Data Analysis.
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  • This chapter of the NIST Engineering Statistics handbook describes the measurement process characterization with discussions of control, calibration, gauge studies, and uncertainty analysis, and a set of case studies.
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  • This chapter of the NIST Engineering Statistics handbook presents information on the statistical modeling of an engineering process. It contains an introduction, discussion of the assumptions, information about data collection and analysis, a discussion of what can be concluded from different process models, and case studies.
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  • This chapter of the NIST Engineering Statistics handbook provides information on the proper design of experiments. It contains an introduction, a discussion of assumptions, a description of different design types, a discussion of the analysis of data, and case studies.
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  • This site is the Statistical Consulting Service Web Resources page for York University. It includes lists of statistical and statistical graphics resources, SAS information guides, online statistical computing applets, and a bibliography of articles for the statistics user.

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  • Free access to selected Internet resources covering all subject areas. This statistics research section includes links to journals, articles, data, and statistical associations.
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  • This site contains data sets to help teach a Chance course and help students understand issues that may not be found in a standard statistics text. Topics covered include: mean, median, random walks, regression, correlation, and more.
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  • This lesson deals with the statistics of political polls and ideas like sampling, bias, graphing, and measures of location. As quoted on the site, "Upon completing this lesson, students will be able to identify and differentiate between types of political samples, as well as select and use statistical and visual representations to describe a list of data. Furthermore, students will be able to identify sources of bias in samples and find ways of reducing and eliminating sampling bias." A link to a related worksheet is included.
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