Reasoning from Data and Chance Summary
Monday - Friday, July 11 - 15, 2011
Greetings PCMIers!! In the second week here at the "ranch," the members of the Reasoning from Data and Chance working group began to hone our focus on a series of small-group projects that we will finish be the end of next week. The four middle school teachers in the group (Sandy, Arden, Jessica and Jemal) have teamed up to create a comprehensive overview of the Common Core Standards in Data and Statistics for middle school teachers. Their hope is to create a teacher resource that summarizes the new standards and gives teachers a head start on instruction with key questions related to the content and suggestions for larger projects, which connect the standards to real life.
Two of the high school teachers on our team (Dee Dee and James) are also tackling the Data and Statistics standards from the Common Core in an attempt to make them relevant to students and teachers at the Algebra 2 level. They hope to produce a final document that summarizes the standards for teachers and offers a rich choice of lessons and/or projects that incorporate technology such as the TI-Nspire handheld and Fathom software.
Another pair of high school teachers in the group (Jason and Sam) is developing a series of investigations into probability and its connection to sporting events. Specifically, they are trying to help students develop an answer to the question: "How unlikely must an outcome be in order for it to be classified as an upset?"
James and Sam are creating a total of four inter-connected lessons, which ultimately lead to students utilizing statistical models in order to make predictions about the outcome of past sporting events. They will then compare their predicted results to the actual outcomes and determine whether the final results could statistically qualify as an upset.
In addition to furthering our work on individual projects, the group also benefited from an outstanding presentation by Gail Burrill on the many data analysis capabilities of the TI-Nspire handheld calculator. After we downloaded a pre-made data set, Gail showed us the many ways that the Nspire can manipulate data for display and dissect data for analysis. For example, as a group, we examined the relationship between the cost of properties on a standard Monopoly board and their distance from GO in order to determine which properties offer the best value.
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This material is based upon work supported by the National Science Foundation under Grant No. 0314808 and Grant No. ESI-0554309. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.