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Statistical Topic

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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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  • April 10, 2007 webinar presented by Maria C. Pruchnicki, The Ohio State University, and hosted by Jackie Miller, The Ohio State University. Distance education and online learning opportunities, collectively known as "e-learning", are becoming increasingly used in higher education. Nationally, online enrollment increased to 3.2 million students in 2005, compared to 2.3 million in 2004. Furthermore, nearly 60% of higher education institutions identify e-learning as part of their long-term education strategy. Newer educational technologies including course management systems and Internet-based conferencing software can be used to both deliver content and engage participants as part of a social learning community. However, even experienced faculty can face pedagogical and operational challenges as they transition to the online environment. This interactive presentation discusses a systematic approach to developing web-based instruction, with an Ohio State University experience as a case example.
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  • November 13, 2007 Teaching and Learning webinar presented by Michael Rodriguez and Andrew Zieffler, University of Minnesota, ad hosted by Jackie Miller, The Ohio State University. This webinar includes an introduction to the idea of assessment for learning - assessments that support learning, enhance learning, and provides additional learning opportunities that support instruction. Several fundamental measurement tools are described to support the development of effective assessments that work.
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  • February 12, 2008 Teaching and Learning webinar presented by Christopher J. Malone, Winona State University and hosted by Jackie Miller, The Ohio State University. The procedural steps involved in completing a statistical investigation are often discussed in an introductory statistics course. For example, students usually gain knowledge about developing an appropriate research question, performing appropriate descriptive and graphical summaries, completing the necessary inferential procedures, and communicating the results of such an analysis. The traditional sequencing of topics in an introductory course places statistical inference near the end. As a result, students have limited opportunities to perform a complete statistical investigation. In this webinar, Dr. Malone proposes a new sequencing of topics that may enhance students' ability to perform a complete statistical investigation from beginning to end.
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  • Webinar recorded May 9, 2006 presented by Carl Lee of Central Michigan University and hosted by Jackie Miller of The Ohio State University. Do you use hands-on activities in your class? Would you be interested in using data collected by students from different classes at different institutions? Would you be interested in sharing your students' data with others? Does it take more time than you would like to spend in your class for hands-on activities? Do you have to enter the hands-on activity data yourself after the class period? If your answer to any of the above questions is "YES", then, this Real-Time Online Database approach should be beneficial to your class. In this presentation, Dr. Lee (1) introduces the real-time online database (stat.cst.cmich.edu/statact) funded by a NSF/CCL grant, (2) demonstrates how to use the real-time database to teach introductory statistics using two of the real-time activities and (3) shares with you some of the assessment activities including activity work sheets and projects.
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  • The AIMS project developed lesson plans and activities based on innovative materials that have been produced in the past few years for introductory statistics courses. These lesson plans and student activity guides were developed to help transform an introductory statistics course into one that is aligned with the Guidelines for Assessment and Instruction in Statistics Education (GAISE) for teaching introductory statistics courses. The lessons build on implications from educational research and also involve students in small and large group discussion, computer explorations, and hands-on activities.
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  • A cartoon that might be used in introducing scatterplots and correlation. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.
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  • This interactive lecture activity motivates the need for sampling. "Why sample, why not just take a census?" Under time pressure, students count the number of times the letter F appears in a paragraph. The activity demonstrates that a census, even when it is easy to take, may not give accurate information. Under the time pressure measurement errors are more frequently made in the census rather than in a small sample.
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  • This activity illustrates the convergence of long run relative frequency to the true probability. The psychic ability of a student from the class is studied using an applet. The student is asked to repeatedly guess the outcome of a virtual coin toss. The instructor enters the student's guesses and the applet plots the percentage of correct answers versus the number of attempts. With the applet, many guesses can be entered very quickly. If the student is truly a psychic, the percentage correct will converge to a value above 0.5.
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