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The Hulme Arch Bridge in Manchester, England is shaped like a parabola. The ends of the arch are 52 meters apart, and it is 25 meters high.
The purpose of this discussion is for students to describe how they can adjust a parabolic function in order to model a situation. Ask 2–3 students to share what aspects of the shape they think Han’s function does and does not model well, recording responses for all to see next to the displayed graph. Invite previously selected students to share their responses comparing the height of Han’s graph and the height of the bridge, starting with students who used a guess and check method and ending with students who calculated a scale factor of since .
Conclude the discussion by telling students that the value 0.037 is often called a scale factor. In this instance, the scale factor compressed the graph vertically by a factor of 0.037 toward the -axis. The only points that didn't move were those already on the -axis, which were the two horizontal intercepts. Had the factor been a number greater than 1, we would say that the graph was stretched vertically away from the -axis.
Graphing technology is needed for every student.
A certain brand of dog food gives the minimum daily amount of food a dog needs depending on its weight. We want to model the relationship between the amount of food and the dog’s weight with a function , where is the amount of food, in grams, needed by a dog weighing pounds.
| dog weight (pounds) | food amount (grams) |
|---|---|
| 5 | 50 |
| 10 | 75 |
| 20 | 130 |
| 40 | 230 |
| 60 | 305 |
| 80 | 375 |
| 100 | 435 |
If students are unsure how to start identifying an appropriate value for , consider saying:
“Tell me more about how a scale factor can transform the output of a function.”
“How could graphing different values of , such as one large, one near 0, and one negative, help you decide on the scale factor?”
The goal of this discussion is for students to understand that if we can recognize the general shape of data (or of an image, as in the previous activity), we can then identify a function type to model the data. Once the function type is known, we can use what we know about graphical transformations to fit a function to the data.
Here are some questions for discussion: