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To Gather
Graphing technology
The purpose of this activity is to review how to create a scatter plot using technology and come up with a function to model the data. This work is similar to the work in the associated Algebra 1 lesson but includes more explicit instructions and steps toward analyzing data and choosing an appropriate model (MP4).
Graphing technology is needed for every student. Display the table of data for all to see, and ask students whether they think a linear or exponential model would be a better fit for this data. After a minute of quiet think time, ask a few students to share their reasoning.
If needed, demonstrate using graphing technology to input the given data and create a scatter plot.
If the graphing technology platform allows it, consider showing students how to create sliders. In Desmos, simply type
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.
To Gather
Graphing technology
This activity is an opportunity to practice some of the discrete skills used in modeling data in two variables with a function. Students decide between different possible models for different sets of data, which is a part of modeling with mathematics (MP4). The first two data sets are more scaffolded because they ask students questions about the type of function that would fit best and the meaning of the numbers in the equation. The other data sets are less scaffolded because they ask students only to develop an equation to model the data directly.
Monitor for students who use these different strategies:
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: