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The goal of this Warm-up is for students to preview and start making sense of the data they will study in this lesson (MP1). The data is for the amount of the moon visible from a particular location on Earth each night over the course of one month. The context is not provided, so students can focus on patterns that they identify in the raw data before attempting to model it with a trigonometric function.
The data is taken for January 2018 in the mountain time zone at midnight (the very beginning of the day).
Display the table. Tell students, “The headings have been removed from these tables of data. What do you think the data could be referring to?”
Give students 1 minute of quiet think time, and then 1 minute to discuss with a partner, followed by a whole-class discussion.
Here is some data that we will study in today’s lesson.
| input | output |
|---|---|
| 1 | 0.99 |
| 2 | 1.00 |
| 3 | 0.98 |
| 4 | 0.93 |
| 5 | 0.86 |
| 6 | 0.77 |
| 7 | 0.67 |
| 8 | 0.57 |
| 9 | 0.46 |
| 10 | 0.37 |
| input | output |
|---|---|
| 11 | 0.28 |
| 12 | 0.19 |
| 13 | 0.13 |
| 14 | 0.07 |
| 15 | 0.03 |
| 16 | 0.01 |
| 17 | 0.00 |
| 18 | 0.01 |
| 19 | 0.04 |
| 20 | 0.09 |
| input | output |
|---|---|
| 21 | 0.16 |
| 22 | 0.24 |
| 23 | 0.33 |
| 24 | 0.43 |
| 25 | 0.54 |
| 26 | 0.65 |
| 27 | 0.76 |
| 28 | 0.85 |
| 29 | 0.92 |
| 30 | 0.98 |
| 31 | 1.00 |
Ask students to share their ideas about what the data could be referring to. Ask them what patterns they noticed that helped them come up with their ideas.
If the overall pattern (the numbers decrease and then increase) does not come up during conversation, ask students to discuss how this is like other situations they have examined in this unit.
The goal of this activity is to model data with a trigonometric function in a context that is not directly about circular motion. The periodic behavior of the amount of the moon visible is governed by the moon’s orbit around Earth and Earth’s orbit around the sun. These orbits can be modeled by ellipses rather than circles, though they are both pretty close to being circular. In this activity, students analyze the data from the Warm-up, making predictions about the amplitude, midline, period, and horizontal translation for a trigonometric model (MP4).
Next students check how well their model fits the actual data and use technology to modify the parameters in their model as needed. Finally, students use their models to make predictions about the moon for later dates in 2018. This prediction work is a very important part of the task, not only because making predictions is one of the main reasons for creating models but also because this can bring out deficiencies that are otherwise not apparent. For example, a 30-day period fits the January data well, but it predicts a full moon on December 28, 2018 when only 62% of the moon is visible. A 29-day period does not fit the January data as well and predicts a full moon on December 16, which is too soon. A 29.5 day period turns out to fit the overall data better than 29 or 30 days, even though it does not seem to fit the January data as well as 30. To the nearest hundredth, the orbit of the moon takes 29.53 days.
For reference as students work on the problems, the next two full moons in 2018 in the mountain time zone (the source of the data) are March 2, 2018 and March 31, 2018. There are a variety of online sites where more data about the moon on specific dates can be retrieved in order for students to check their birthday predictions.
If students do not have access to Desmos, they can experiment with the different parameters in their trigonometric model using other graphing technology. Some students may also use technology to propose a trigonometric model for the data.
Graphing technology is needed for every student.
Tell students that the data from the Warm-up is the amount of the moon that is visible from a particular location on Earth at midnight for each day in January 2018. If possible, use a flashlight and a sphere to demonstrate for students what causes different amounts of the moon to be visible. At any given moment in time, half of the moon is illuminated by the sun (the half “facing” the sun) and half is dark. When we see a full moon, that means the part of the moon illuminated by the sun is facing our location on Earth, and when we see little or none of the moon, that means the dark half of the moon is facing us. As the moon orbits Earth and Earth orbits the sun, the relative positions of the three bodies change, and this produces the moon cycle investigated in this activity.
Instruct students to record “day” as the header of the input column of the data tables and to record “amount visible” in the output column of the data tables.
Highlight these features of the moon data:
Ask students how they used the midline, amplitude, and estimated period in their equation. For the equation , the added constant is the midline while the coefficient of 0.5 is the amplitude. This means that the graph will be horizontally centered at 0.5 (half of the moon visible) with a maximum of (all of the moon visible) and a minimum of (none of the moon visible). The denominator of 29 in the expression gives the function a period of 29. The term is a horizontal translation to the right by 1 so that the maximum (full moon) is predicted for January 2, one day after January 1.
Discuss how well the models worked for predicting the fraction of the moon visible for dates further out in the year. The models should work well for January and the next couple months but the further out you go, the period begins to be off (for a choice of 29 or 30 days). This makes sense because a small error in the period becomes more pronounced with each cycle through. Ask students what they might do to better estimate the period of the moon’s orbit around Earth. Looking at the table shows that the time between full moons consistently alternates between 29 and 30 days, making 29.5 days an appropriate estimate for the period.
If time allows, ask students:
A key point to highlight here is that with a given set of data it is not always possible to produce an accurate model.
Sometimes a phenomenon can be periodic even though it is not connected to motion in a circle. For example, here is a graph of the water level in Bridgeport, Connecticut, over a 50-hour period in 2018.
The midline of the graph appears to be around 4.5 feet. Notice that each day (or each 24-hour period) there are two high tides, a small one where the water goes up by a little less than 3 feet and then a bigger one when the tide goes up by a little more than 3 feet. Since there are two high tides per day, the period for this graph is about 12 hours. The data begins about 1 hour before the tide is at the 4.5 midline value. Since , this would make the sine function a good choice for modeling the tide.
Putting together all of our information gives the model , where measures hours since midnight on September 1.
Notice that:
The data is the amount of the moon that is visible from a particular location on Earth at midnight for each day in January 2018. A value of 1 represents a full moon in which all of the illuminated portion of the moon's face is visible. A value of 0.25 means that one-fourth of the illuminated portion of the moon's face is visible.
If students struggle with the horizontal translation in their function that models the amount of the moon that is visible, consider saying:
“Tell me more about the amplitude, midline, and period for your model.”
“Try writing and graphing your model without the horizontal translation. How does the maximum of your model compare to where you want the maximum to occur?"