Lecture Examples

  • A sketch by Anastasia Mandel reinterpreting View of Mount Fuji by Utagawa Hiroshige (1859) with the statistical caption "Survival analysis." This is part of a collection of sketches by Anastasia Mandel and their accompanying statistical captions discussed in the paper "How art helps to understand statistics" (Model Assisted Statistics and Applications, 2009) by Stan Lipovetsky and Igor Mandel in volume 4 pages 313-324. Free to use in classrooms and on course websites.
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  • A sketch by Anastasia Mandel reinterpreting Valencian Fisherman by Joaquin Sorolla y Bastida (1895) with the statistical caption "Networking, not neural yet." This is part of a collection of sketches by Anastasia Mandel and their accompanying statistical captions discussed in the paper "How art helps to understand statistics" (Model Assisted Statistics and Applications, 2009) by Stan Lipovetsky and Igor Mandel in volume 4 pages 313-324. Free to use in classrooms and on course websites.
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  • Share with your students why the presence of an outlier affects which measure of central tendency to report. Feel free to modify this Powerpoint presentation to fit the needs of your students. Included at the end are additional online resources to further engage your students in their learning about the mean, median, and mode. The presentation is covered by a Creative Commons Attribution-Share Alike 3.0 License.

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  • This is a collection of notes that covers many topics typically included in introductory and/or intermediate statistics courses. The notes are in PDF format, and each is followed by a set of exercises (with most answers included). The site also includes some tables and a link to a StatTable calculator.
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  • This is a site that contains a number of types of material that can be used in teaching about chance and probability. Lesson plans, syllabi, suggested activities, and data sets are available. The data sets contain interesting information for students such as: quarterback passing rating data, baseball streaks, and baseball salaries that can be used to illustrate means, medians, etc.. The site also contains a link to the Chance News (which is now a wiki on CAUSEweb).

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  • In this module, students can test their knowledge of levels of measurement by attempting to determine the the level of measurement of ten different variables. For each variable, a statement is also provided and students can indicate whether the statement about the variable is valid or invalid (given the way in which the variable was measured). There is also a brief "refresher" included here about levels of measurement.

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  • This is a collection of cases to demonstrate concepts of inferential statistics. Many materials are flash based, which is specifically interesting for young and beginning learners. This resource provides a simple introduction to probability and to Type I and II errors.
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  • January 26, 2010 webinar presented by Alicia Gram, Smith College, and hosted by Leigh Slauson, Capital University. This webinar describes an activity that uses data collected from an experiment looking at the relationship between two categorical variables: whether a cotton plant was exposed to spider mites; and did the plant contract Wilt disease? The activity uses randomization to explore whether there is a difference between the occurrence of the disease with and without the mites. The webinar includes a discussion of the learning goals of the activity, followed by an implementation of the activity then suggestions for assessment. The implementation first uses a physical simulation, then a simulation using technology. (Extra materials, including Fathom instructions for the simulation, available for download free of charge).

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  • The two worksheets enable instructors to demonstrate how changes in the magnitude of the treatment effects and of the standard deviation of the error term will impact significance in a One-Way ANOVA model. The user specifies three input values that influence the simulation of random observations. ANOVA calculations are provided for the student, leaving the focus on the interpretation of the results. The mirror site (found at http://misnt.indstate.edu/cmclaren/ANOVA_Note.doc) contains an article that can serve as a teaching note to accompany the worksheets.
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  • Probability plotter and calculator allows students to explore different distributions and their relationships. Interactive dialogue box allows students to change distribution shape and scaling parameters as well as allowing to explore cumulative probabilities. Discrete distributions include the discrete uniform, binomial, and the poisson. Continuous distributions include the uniform, beta, exponential, weibull, gamma, and lognormal distributions. Sampling distributions include the normal, the t-distribution, the chi-square, and the F-distribution.
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