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  • Funded by the National Science Foundation, workshops were held over a three-year period, each with about twenty participants nearly equally divided between mathematics educators and statisticians. In these exchanges the mathematics educators presented honest assessments of the status of mathematics education research (both its strengths and its weaknesses), and the statisticians provided insights into modern statistical methods that could be more widely used in such research. The discussions led to an outline of guidelines for evaluating and reporting mathematics education research, which were molded into the current report. The purpose of the reporting guidelines is to foster the development of a stronger foundation of research in mathematics education, one that will be scientific, cumulative, interconnected, and intertwined with teaching practice. The guidelines are built around a model involving five key components of a high-quality research program: generating ideas, framing those ideas in a research setting, examining the research questions in small studies, generalizing the results in larger and more refined studies, and extending the results over time and location. Any single research project may have only one or two of these components, but such projects should link to others so that a viable research program that will be interconnected and cumulative can be identified and used to effect improvements in both teaching practice and future research. The guidelines provide details that are essential for these linkages to occur. Three appendices provide background material dealing with (a) a model for research in mathematics education in light of a medical model for clinical trials; (b) technical issues of measurement, unit of randomization, experiments vs. observations, and gain scores as they relate to scientifically based research; and (c) critical areas for cooperation between statistics and mathematics education research, including qualitative vs. quantitative research, educating graduate students and keeping mathematics education faculty current in education research, statistics practices and methodologies, and building partnerships and collaboratives.

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  • The Islands is a free, innovative, online virtual human population created by Dr Michael Bulmer from the University of Queensland. The Islands supports the teaching of statistics through data investigations by providing students with a realistic virtual world where they can propose statistical questions, design investigations and collect the necessary data for statistical analysis and interpretation. The wide range of data and tasks available on the Islands caters to many scientific areas and student interests. Must create an account to access this virtual world.

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  • A quick "hands on" activity for an in-class experience of data collection as a simple linear regression example where students  predict the time needed for a human chain of hand squeezes to make a full circuit as a function of number of people in the chain.  The lesson plan  secondary school lesson plan adapted from Cynthia Lanius’ hand squeeze activity by Bo Brawner at Tarleton State University.

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  • This limerick was written by Dr. Nyaradzo Mvududu of the Seattle Pacific University School of Education. The poem was given an honorable mention in the 2007 A-Mu-sing competition.

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  • This poem was written by Peter E. Sprangers while he was a graduate student in the Department of Statistics at The Ohio State University and published in "CMOOL: Central Moments Of Our Lives" (volume 1; 2006, issue 2). The poem took second place in the poetry category of the 2007 A-Mu-sing competition.

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  • This case study starts by the simple comparison of the prices of houses with and without fireplaces and extends the analysis to examine other characteristics of the houses with fireplace that may affect the price as well. The intent is to show the danger of using simple group comparisons to answer a question that involves many variables. The lesson shows the R code for doing this analysis; however, the data and the model could be used with another statistical software.

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  • Explore the Hubble Deep Fields from a statistical point of view.  Watch out for the booby traps of bias, the vagueness of variability, and the shiftiness of sample size as we travel on a photo safari through the Hubble Deep Fields (HDFs).

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  • This lesson introduces students to creating spreadsheets for statistical analysis.

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  • This program focuses on the teamwork required to produce a successful mission and the importance of statistics in project design and management. Using the video and a hands-on lesson, students learn about statistical analysis and how people use statistics, such as mean, median, mode and range, to make decisions. Members of the Penske Racing Team and engineers from Pratt & Whitney Rocketdyne help students investigate the relationship between work, energy and power as they look at race car design, the space shuttle and the International Space Station.

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  • This page will perform a two-way factorial analysis of variance for designs in which there are 2-4 levels of each of two variables, A and B, with each subject measured under each of the AxB combinations.

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