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  • March 23, 2010 Activity webinar presented by John Gabrosek & Paul Stephenson, Grand Valley State University and hosted by Leigh Slauson, Capital University. GOLO is a dice-based golf game that simulates playing a round of golf. GOLO can be used to illustrate basic probability concepts, descriptive summaries for data, discrete probability distributions, order statistics, and game theory. Participants had a chance to play the online version of GOLO.
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  • April 27, 2010 Activity webinar presented by Shonda Kuiper, Grinnell College, and hosted by Leigh Slauson, Capital University. Educational games have had varied success in the past. However, what it means to incorporate games into the classroom has changed dramatically in the last 10 years. The goals of these games are to 1) foster a sense of engagement, 2) have a low threat of failure, 3) allow instructors to create simplified models of the world around us, and 4) motivate students to learn. This webinar uses the same reaction time game to demonstrate a simple 1- 2 day activity that is appropriate for introductory courses as well as an advanced project that encourages students to experience data analysis as it is actually practiced in multiple disciplines. In the introductory activity students are asked to spend 15 minutes playing an on-line game. Data collected from the game is used to demonstrate the importance of proper data collection and appropriate statistical analysis. The advanced project asks students to read primary literature, plan and carry out game based experiments, and present their results.
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  • An important idea in statistics is that the amount of data matters. We often teach this with formulas --- the standard error of the mean, the t-statistic, etc. --- in which the sample size appears in a denominator as √n. This is fine, so far as it goes, but it often fails to connect with a student's intuition. In this presentation, I'll describe a kinesthetic learning activity --- literally a random walk --- that helps drive home to students why more data is better and why the square-root arises naturally and can be understood by simple geometry. Students remember this activity and its lesson long after they have forgotten the formulas from their statistics class.
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  • August 25, 2009 Activity webinar presented by Michelle Everson, University of Minnesota and hosted by Leigh Slauson, Capital University. In a classroom setting, students can engage in hands-on activities in order to better understand certain concepts and ideas. Replicating hands-on activities in an online environment, however, can be a challenge for instructors. The purpose of this webinar is to present an applet that was created to replicate a "Post-it Note" activity commonly used in classroom sections of an undergraduate introductory statistics course at University of Minnesota. The Post-it Note activity is meant to help students develop a more conceptual understanding of the mean and the median by moving a set of Post-it Notes along a number line. During the webinar, participants have an opportunity to see and experience just how online students are able to interact with an applet named the "Sticky Centers" applet, and the webinar presents the kinds of materials and assignments that have been created to use in conjunction with this applet. The webinar ends with a preview of a newer applet that is being developed in order to replicate the famous "Gummy Bears in Space" activity (presented in Schaeffer, Gnanadesikan, Watkins & Witmer, 1996). A supplemental student handout is available for download free of charge.
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  • Many introductory Statistics courses consist of two main components: lecture sections and computer laboratory sections. In the computer labs, students often review fundamental course concepts, learn to analyze data using statistical software, and practice applying their knowledge to real world scenarios. Lab time could be better utilized if students arrived with 1) prior exposure to the core statistical ideas, and 2) a basic familiarity with the statistical software package. To achieve these objectives, PreLabs have been integrated into an introductory statistics course. A simple screen capture software (Jing) was used to create videos. The videos and a very short corresponding assignment together form a PreLab and are made available to students to access at appropriate times in the course. Some PreLabs were created to expose the students to statistical software details. Other PreLabs incorporate an available online learning resource or applet which allows students to gain a deeper understanding of a course concept through simulation and visualization. Not all on-line learning resources are ready to use 'as in' in a course. Some may be lacking a preface or description on how they are to be used; others may use slightly different notation or language than your students are accustomed to; a few may even contain an error or item that needs some clarification. One solution to such difficulties was to create a video wrapper so students can see how the applet works while receiving guidance from the instructor. In this webinar we will share the success story of how one introductory Statistics course integrated these video wrappers into the course and the discuss other possible applications.
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  • September 22, 2009 Activity Webinar presented by Diane Evans, Rose-Hulman Institute of Technology and hosted by Leigh Slauson, Capital University. This webinar is based on an activity found at www.lhs.logan.k12.ut.us/~jsmart/tank.htm and other on-line resources (see references). During World War II, the British and U.S. statisticians used estimation methods to deduce the productivity of Germany's armament factories using serial numbers found on captured equipment, such as tanks. The tanks were numbered in a manner similar to 1, 2, 3, ..., N, and the goal of the allies was to estimate the population maximum N from their collected sample of serial numbers. The purpose of this activity is to introduce students to the concept of an unbiased estimator of a population parameter. Students develop several estimators for the parameter N and compare them by running simulations in Minitab. Extra materials available for download free of charge.
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  • It's Just STATA Code To Me is a song written by Dorry Segev of Johns Hopkins University that reflects on a number of issues in biostatistical data analysis. The song may be sung to the tune of Billy Joel's 1980 hit song "It's Still Rock and Roll To Me." The lyrics were written for Marie DIener-West's Biostatistics 653 course at Johns Hopkins that regularly asks students to create songs, videos, and poetry with biostatistics themes.
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  • May 26, 2009 Activity webinar presented by Dennis Pearl, The Ohio State Unversity, and hosted by Leigh Slauson, Otterbein College. This webinar describes a computer lab activity using the Flash-based applet at www.causeweb.org/mouse_experiment to teach key principles regarding the value of random assignment. These include: 1) how it helps to eliminate bias when compared with a haphazard assignment process, 2) how it leads to a consistent pattern of results when repeated, and 3) how it makes the question of statistical significance interesting since differences between groups are either from treatment or by the luck of the draw. In this webinar, the activity is demonstrated along with a discussion of goals, context, background materials, class handouts, and assessments.
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  • June 23, 2009 Activity webinar presented and hosted by Leigh Slauson, Otterbein College. This webinar describes an activity that uses the playlist from an iPod music player to teach the concept of random selection, the various sampling techniques, and the use of simulation to estimate probability. The webinar includes a discussion of the background of this activity, the learning goals of the activity, how this activity can be adapted to different levels of technology, suggestions for assessment, and other supplemental reference materials. (handouts and other materials available for free download)
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  • July 28, 2009 Activity webinar presented by Jo Hardin, Pomona College, and hosted by Leigh Slauson, Otterbein College. Based on an activity by John Spurrier, this webinar uses a baseball example to introduce students to Bayesian estimation. Students use prior information to determine prior distributions which lead to different estimators of the probability of a hit in baseball. The webinar also compares different Bayesian estimators and different frequentist estimators using bias, variability, and mean squared error. The effect that sample size and dispersion of the prior distribution have on the estimator is then illustrated by the activity.
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