Professional

  • Although numbers don't lie, it's rather annoying that they don't tell us everything we need to know. Maybe it's because 99% of all statistics only tell us 49% of the story. is a quote by American investment author Ron DeLegge II (1971 - ). The quote appears in his book "Gents With No Cents" published in 2011 by Half Full Publishing Group.

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  • This issue contains articles on: The advantages and pitfalls of using online panel research, including a discussion of improving data quality and designing the survey research strategically, sequential sampling and testing in a "simple against simple" situation, including a description of Abraham Wald's historical and theoretical contributions to the theory, and R code for running simulations, and the experience and results of an exit poll conducted by two students in Washington D.C. during the 2008 presidential election.
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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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  • 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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  • October 14, 2008 Teaching and Learning webinar presented by Daniel Kaplan, Macalester College and hosted by Jackie Miller, The Ohio State University. George Cobb describes the core logic of statistical inference in terms of the three Rs: Randomize, Repeat, Reject. Note that all three Rs involve process or action. Teaching this core logic is more effective when students are able to carry out these actions on real data. This webinar shows how to use computers effectively with introductory-level students to teach them the three Rs of inference. This is done with another R: the statistical software package. The simulations that are carried out involve constructing confidence intervals, demonstrating the idea of "coverage," hypothesis testing, and confounding and covariation.
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  • The idea that the examination of a relatively small number of randomly selected individuals can furnish dependable information about the characteristics of a vast unseen universe is an idea so powerful that only familiarity makes it cease to be exciting Is a quote from American Educational Statistician Helen Mary Walker (1891 - 1983). Helen Walker was the first women to serve as the president of the American Statistical Association and this quote is from her December 27, 1944 presidential address at the 104th annual meeting of the ASA in Washington, D.C. The full address may be found in the "Journal of the American Statistical Association" (1945; vol. 40, #229 p. 1-10).

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  • A cartoon to teach the idea that sampling variability depends on the size of the sample, and not on the size of the population (as long as the sample is a small part of the population). Cartoon drawn by British cartoonist John Landers based on an idea from Dennis Pearl. Free to use in the classroom and for course websites.

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