# Gas Guzzlers

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## Objective

SWBAT to organize data, write a function that represents the data algebraically, and then use that function to predict other data.

#### Big Idea

In this activity, students will organize given data about cars and their respective mpg to determine a function that represents data. Then, using the function, the student has to determine the likely mpg of a car model not displayed in the data.

## Warm Up

5 minutes

For today's Warm Up, I provided a graph and a context and asked the students to decide if the two agree.  When the timer sounds, I ask students to share their ideas with their table mates. This allows students time to verbalize their thinking which typically strengthens responses from students when I call on them.

When polled, half the class believed the graph matched the scenario and were able to label the graph based on what was happening:  tub filling with water, kid getting in, kid staying in, kid letting the water out of the tub.  There was some discussion about whether most people stay in the tub while the water runs out.  For those students, I asked how the graph should change to show the kid got out.  A student came to the smartboard and wrote his idea for the graph on top of the given one (in a different color) and his table mates agreed.

This will certainly lead to 8.F.A.2. which expects students to compare two different functions given a variety of representations.

## Gas Guzzlers

30 minutes

In today's activity, students must organize given data into a table, graph the data on a coordinate grid, create a line of best fit, and then determine the equation/rule for the data. Once a rule is determined, the student will use it to find the expected mpg for a 2009 model year car.

I expect students to be able to complete this task in 30 minutes or less since we have practice the required skills several times in this unit.

## Closure

10 minutes

Because students collaborated on today's assignment, I was interested in seeing who can apply the function rule independently as well so I posed a new problem for them to answer as a ticket out the door (on note cards): Use the function from your data to predict the mpg a 2014 model year car would likely have.