March 12, 2009
Deb Hughes Hallett drew on her experience working with the Harvard Kennedy School and with her interest and expertise in quantitative analysis to provide explorations with decision analysis. Participants grappled with case studies as they practiced organizing decision aspects into factor trees with chance nodes and decision boxes. The case studies included probabilities of events occuring and costs of particular outcomes. From the given information, expected values were calculated. Decision trees provided a format to choose outcomes.
The ideas and strategies presented were beyond the norm of high school mathematics, yet numerous standards were addressed.
Some of the AIMS Standards included are:
1.2.1 Solve contextual problems using exact numbers or estimates where appropriate.
1.3.1 Recognize the limitations of estimations by assessing the amount of error resulting from estimation and determining whether the error is within acceptable tolerance limits.
1.3.4 Determine when an estimate is more appropriate than an exact answer.
2.1.5 Organize data into an appropriate graphical representation.
2.1.6 Evaluate the reasonableness of conclusions drawn from data analysis.
2.2.5 Explain the concept of and calculate expected value for propbability.
2.3.2 Apply appropriate means pf computing the number of possible arrangements of the items in each case to solve problems by distinguishing between situations where order matters.
2.3.3 Determine the number of possible outcomes of an event.
3.1.3 Solve problems involving recursion.
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| Deb introduces thefoundations of decision analysis. | Ginger Ververelli and Jeannie Arbogast work together on a problem. |
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| A group works together to draw the decision tree diagram. | Deb discusses the tree nodes. |
