Unit Purpose: Clustering is the process by which discrete objects can be assigned to groups which have similar characteristics. Clustering can be used to group like species, survey results, or satellite image data. By learning to use a clustering algorithm, the student acquires a tool which will allow him to analyze a variety of data. Unit Objective: To develop and use a MATLAB program to cluster data points. Unit Overview: A clustering algorithm used to find clusters of points based on the distance formula will be introduced. The student will use the algorithm and a calculator to find the clusters in a sample set of data points. Then the student will be ready to use the MATLAB program provided to determine the clusters; some students may wish to learn the MATLAB language in order to modify the code. Materials: A calculator and the MATLAB application Mathematical Concepts: The distance formula applied to points in two-dimensional or higher space. Links to State Science and Mathematics Outcomes: Students will demonstrate the ability to apply scientific models to life science, physical science, and earth/space science problems. Students will demonstrate the ability to use technology to solve real world problems. Student Outcomes: The student will be able to apply the clustering algorithm to a variety of problems. Some students may develop modifications to the algorithm to tailor it to special cases. Activities: A Clustering Algorithm The MATLAB Code Student Assessments: Ask the student to cluster a set of two-dimensional data points using the MATLAB program. Ask the student to find examples of data for which clustering would be a valuable tool. Ask the student to modify the MATLAB code to cluster 3-dimensional data points and plot them. Ask the student to create a new clustering algorithm.

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