Joint Mathematics Meetings - January 6 - 9, 2008 - Sunday - Wednesday - San Diego Convention Center

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MAA Ancillary Workshops

Introducing Concepts of Statistical Inference, Saturday, 8:30 a.m. to 5:00 p.m., presented by Allan Rossman and Beth Chance, California Polytechnic University-San Luis Obispo; George Cobb, Mount Holyoke College; and John Holcomb, Cleveland State University. We present ideas and activities for helping students to learn fundamental concepts of statistical inference. These ideas and activities are centered around a randomization-based curriculum rather than normal-based inference; they rely heavily on simulations, both tactile and computer-based. Our goals with this curriculum are to develop students' understanding of the process of statistical investigations and of key concepts of inference, rather more covering a litany of specific methods based on normal approximations. We propose that this approach leads to deeper conceptual understanding, makes a clear connection between study design and scope of conclusions, and provides a powerful and generalizable analysis framework. This hands-on workshop will feature participants working directly with student activities, which they can then implement in their own classrooms. We will also discuss ideas for assessing student understanding and invite participants to contribute to an ongoing assessment/evaluation project. The intended audience for this workshop is teachers of introductory statistics in colleges (including two-year colleges) and high schools.

For registration and additional details go to http://www.causeweb.org/workshop/inference_jmm08/. Participants will be notified of the exact meeting room in the San Diego Convention Center. There is no registration fee for this workshop. Lunch will be provided. Enrollment is limited to 30. This workshop is sponsored by MAA Special Interest Group on Statistics Education and the Consortium for the Advancement of Undergraduate Statistics Education (CAUSE).

Building (UP) an Undergraduate Statistics Program, Saturday, 8:30 a.m. to 5:00 p.m., presented by Julie Legler, St. Olaf College, and Robin Lock, St. Lawrence University. Many colleges and universities are recognizing that this is an opportune time to establish or invigorate an Undergraduate Statistics Program or USP (i.e., programs that offer majors in statistics as well as those offering statistics minors, concentrations or tracks within other majors). Is this a good time for your department to strengthen its statistics program? This workshop will explore this question and provide some useful information with respect to enhancing your USP. The Workshop takes a two pronged approach to USP planning. First, participants will use resources to assess the potential and to facilitate planning for a USP at their institution. The resources will include ASA Undergraduate Statistics Education Initiative (USEI) which provides valuable, thoughtful guidance for institutions creating or developing USPs. In addition to examining the USEI guidelines, the workshop will include sharing the experience of a number of successful undergraduate statistics programs, identifying issues your department may face, discussing and proposing solutions, and constructing a plan for your own department. This workshop will address issues related to curriculum and course development, especially beyond the introductory level, as well as some of the many practical, administrative issues institutions face when considering initiating or enhancing a USP. The intended audience for this workshop is faculty and chairs/representatives of mathematics departments looking to establish or invigorate an undergraduate statistics program.

For registration and additional details go to http://www.causeweb.org/workshop/statsprog_jmm08/. Participants will be notified of the exact meeting room in the San Diego Convention Center. There is no registration fee for this workshop. Enrollment is limited to 30. Lunch will be provided. This workshop is sponsored by MAA Special Interest Group on Statistics Education and the Consortium for the Advancement of Undergraduate Statistics Education (CAUSE).

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