Simulation

  • 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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  • StatKey is the analysis package to accompany the textbook "Statistics: Unlocking the Power of Data." StatKey includes interactive applets to describe and graph data, engage in bootstrapping and randomization tests, and explore sampling distributions and theoretical distributions.
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  • A joke that can be used when teaching six sigma process control ideas or chi-squared goodness-of-fit tests.
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  • This is an extensive collection (and a continuously expanding collection) of applets on topics that include probability, descriptive statistics, sampling distributions, Monte Carlo simulation, Buffon's coin problem, chi-square, p-values, correlation, and more. There is even a random number generator that is part of the collection.
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  • August 10, 2010 T&L webinar presented by Diane Fisher (University of Louisiana at Lafayette), Jennifer Kaplan (Michigan State University), and Neal Rogness (Grand Valley State University) and hosted by Jackie Miller(The Ohio State University). Our research shows that half of the students entering a statistics course use the word random colloquially to mean, "haphazard" or "out of the ordinary." Another large subset of students define random as, "selecting without prior knowledge or criteria." At the end of the semester, only 8% of students we studied gave a correct statistical definition for the word random and most students still define random as, "selecting without order or reason." In this session we will present a classroom approach to help students better understand what statisticians mean by random or randomness as well as preliminary results of the affect of this approach.
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  • September 14, 2010 T&L webinar presented by Thomas Moore(Grinnell College) and hosted by Jackie Miller(The Ohio State University). Permutation tests and randomization tests were introduced almost a century ago, well before inexpensive, high-speed computing made them feasible to use. Fisher and Pitman showed the two-sample t-test could approximate the permutation test in a two independent groups experiment. Today many statistics educators are returning to the permutation test as a more intuitive way to teach hypothesis testing. In this presentation, I will show an interesting teaching example about primate behavior that illustrates how simple permutation tests are to use, even with a messier data set that admits of no obvious and easy-to-compute approximation.
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  • October 12, 2010 T&L webinar presented by George Cobb(Mount Holyoke College) and hosted by Leigh Slauson (Capital University). What's the best way to introduce students of mathematics to statistics? Tradition offers two main choices: a variant of the standard "Stat 101" course, or some version of the two-semester sequence in probability and mathematical statistics. I hope to convince participants to think seriously about a third option: the theory and applications of linear models as a first statistics course for sophomore math majors. Rather than subject you to a half-hour polemic, however, I plan to talk concretely about multiple regression models and methodological challenges that arise in connection with AAUP data relating faculty salaries to the percentage of women faculty, and to present also a short geometric proof of the Gauss-Markov Theorem.
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  • November 9, 2010 T&L webinar presented by Jiyoon Park and Audbjorg Bjornsdottir (University of Minnesota) and hosted by Jackie Miller (The Ohio State University). This webinar presents the development of a new instrument designed to assess the practices and beliefs of teachers of introductory statistics courses. The Statistics Teaching Inventory (STI) was developed to be used as a national survey to assess changes in teaching over time as well as for use in evaluating professional development activities. We will describe the instrument and the validation process, and invite comments and suggestions about its content and potential use in research and evaluation studies.
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  • This site contains a small collection of videos about how to use Minitab.
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