Statistical Inference & Techniques

  • Avoid Linear extrapolation ... The turkey's first 1000 days are a seemingly unending succession of gradually improving circumstances confirmed by daily experience. What happens on Day 1001? Thanksgiving. The quote is by John E. Sener (1954 - ) of Sener Learning services found in the on-line article "Strategies for Effective `20/20 Vision` -- #1: Avoid Linear Extrapolation" at www.senerlearning.net/?q=node/176. The quote is paraphrasing the turkey metaphor made famous by Bertrand Russell and Nassim Nicholas Taleb.
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  • This joke can be used in a discussion of how sample size affects the reliability of the sample mean. The joke may be found amongst the extensive Science Jokes resources at www.newyorkscienceteacher.com
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  • In earlier times they had no statistics and so they had to fall back on lies. This is a quote by Canadian economist Stephen Leacock (1869 - 1944). The quote is found on page 265 of his 1938 book "In Model Memoirs and Other Sketches from Simple to Serious"
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  • December 12, 2006 webinar presented by Michelle Everson, University of Minnesota, and hosted by Jackie Miller, The Ohio State University. This webinar focuses on describing an introductory statistics course that is taught completely online. The structure of this course is described, and samples of different student assignments and activities are presented. Assessment data and student feedback about the course are also presented. Discussion focuses on issues that must be considered when developing and administering an online course, such as the instructor's role in the online course and ways to create an active learning environment in an online course.

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  • January 9, 2007 webinar presented by Sterling Hilton, Brigham Young University, and hosted by Jackie Miler, The Ohio State University. Beginning in January 2005, the ASA (with support from the National Science Foundation) started a series of three workshops for statisticians and mathematics education researchers. The purpose of these workshops was to make recommendations on ways to promote high-quality education research that can stand up under the scrutiny of other scientific communities and that will allow work to be compared and combined across research programs. A draft version of the final report from these workshops entitled "Using Statistics Effectively in Mathematics Education Research" has been written. This webinar summarizes the major points of this report and discuss their relevance to researchers in statistics education.

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  • February 13, 2007 webinar presented by Jim Albert, Bowling Green State University, and hosted by Jackie Miller, The Ohio State University. An introductory statistics course is described that is entirely taught from a baseball perspective. This class has been taught as a special section of the basic introductory course offered at Bowling Green State University . Topics in data analysis are communicated using current and historical baseball datasets. Probability is introduced by describing and playing tabletop baseball games. Inference is taught by distinguishing between a player's "ability" and his "performance", and then describing how one can learn about a player's ability based on his season performance. Baseball issues such as the proper interpretation of situational and "streaky" data are used to illustrate statistical inference.

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  • March 13, 2007 webinar presented by Andrew Zieffler, University of Minnesota, and hosted by Jackie Miller, The Ohio State University. The interdisciplinary field of inquiry that is statistics education research spans a diverse set of disciplines and methodologies. A recent review of a subset of this literature, the research on teaching and learning statistics at the college level, was used to raise some practical issues and pose some challenges to the field of statistics education. These are addressed in this CAUSE webinar. In addition, a recent doctoral dissertation study is used to illustrate some of these challenges and offer suggestions for how to deal with them.

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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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  • May 8, 2007 webinar resented by Bill Notz, The Ohio State University, and hosed by Jackie Miller, The Ohio State University. In this webinar Bill Notz, the Editor of the Journal of Statistics Education (JSE), discusses all aspects of the journal. He outlines the mission and history of the JSE, describes the various departments of the journal, explains what you can find at the journal's web site, indicates the types of manuscripts the journal seeks to publish, and mentions possible future directions.

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  • June 12, 2007 webinar presented by Rob Carver, Stonehill College, and hosted by Jackie Miller, The Ohio Sate University. We've probably all observed that some of our students become positively irritated with the uncertainty that remains after solving a problem of statistical inference. This webinar reports on a continuing empirical investigation of the relationship between Ambiguity Tolerance (AT) and students' facility in developing the skills of inferential reasoning. This research uses some validated measures of AT and of statistical thinking to focus on ambiguity tolerance as an explanatory or moderating factor in learning to apply the techniques of inference.

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