Testing the Model Class: 11th and 12th grade Mathematical Statistics. Materials: Access to a computer, with available connection to the Internet. Access to Microsoft Excel. Calculator. Disk with collected data, as provided by Biology and Chemistry classes. Ozone predicting equation, as formulated in previous lesson, “Building the Model.” Prior Knowledge Needed for Students: Students have completed prior activity, “Building the Model.” Students should be familiar with Microsoft Excel, i.e. be able to input data, manipulate data/columns, etc. Students should have had a basic introduction to statistical analysis (prior WebQuest activity). Also, the students should have an understanding of the following terms: intercept coefficients error t-test t-value p-test 2 p-value R value adjusted R2 value The students should be able to define these terms and know how they relate to making a good model. Objectives: Students will use the ozone predicting equation to predict and display ozone values. Students will compare predicted ozone with actual ozone values. Procedures: Students will be adding a column to their existing data which will display predicted ozone values for that data. Have students add a column labeled Predicted Ozone after the Ozone column in their data set. In the first cell under Predicting Ozone, students will now type in their formula for predicting ozone, substituting their values for intercept, coefficients, and error: = µ + β1*D2 + β2*E2 + β3*F2 – e When the students hit Enter, the predicted ozone value for that set of data will be displayed. Have the students click and drag, the bottom right corner of the cell, all the way to the bottom of their data set. This will automatically calculate all the predicted ozone values for the entire data set! Summarize the Activity: Ask the students: Compare the Ozone and Predicted Ozone columns. In your own words, how “good” of a predictor is your equation? How do you know that? Compare the data on the dates when your predicted ozone was very close to the actual ozone. Compare the data on the dates when your predicted ozone was not very close to the actual ozone. Try to get the students to realize: The dates when the predicted ozone is close to the actual ozone and the dates when the predicted ozone is not close to the actual ozone have certain things in common with one another. As the semester goes on and the more data that is collected and analyzed, the more accurate their ozone predictor formula will be come. Have the students keep this activity in their Data Analysis Journal so they can refer to it during upcoming analyses.
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