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In the spring, an agave plant sends up a flower spike. Here are some data collected from an agave plant in a garden in Tucson, AZ, starting on April 2:
| day | height in inches |
|---|---|
| 0 | 17 |
| 1 | 23 |
| 2 | 29 |
| 3 | 37 |
| 4 | 45 |
| 5 | 52 |
| 6 | 62 |
| 7 | 70 |
| 8 | 80 |
The purpose of this discussion is to compare the equation models students created. Display the scatter plot using technology. Graph some of the different equations students used as models. Here are some questions for discussion:
Invite students to share their responses to the last three questions.
Data Set A shows the height in feet of some buildings and the number of floors in each building. Would a linear or exponential model be a better fit?
Data Set B shows the results of using the “enlarge by 25%” feature on a copy machine several times on a photo. The width in centimeters of the photo is measured after each copy is made. Would a linear or exponential model be a better fit?
| day | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
|---|---|---|---|---|---|---|---|---|---|
| height in inches | 34 | 44 | 52 | 61 | 68 | 74 | 83 | 91 | 97 |
| number of cubes | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|
| number of rolls | 5 | 29 | 140 | 794 | 3,861 |
The goal of this discussion is to compare methods of creating models based on data sets.
Display 2–3 approaches from previously selected students for all to see. Use Compare and Connect to help students compare, contrast, and connect the different approaches. Here are some questions for discussion:
Continue the discussion, focusing on how students decided on the model to use for Data Sets C and D.
Ask students what features they would expect in a good linear or exponential model. Important responses include: