In this lesson, you will design a procedure to test the independent variable of your choice to determine how that independent variable affects the overall percent crush (your dependent variable) of a pop can.

You will collect data in class over several class periods. You will create a graph of that data, analyze your graph, and use a simulation to check the validity of your data. After checking the validity of your data, you will compose a claim based on your data.

You will be asked to support your claim with evidence, and finally asked to explain why your evidence supports your claim using scientific reasoning.

Below is a video of your instructor crushing a can (this will also be demonstrated in class) and a video demonstration of the can crush simulation you will be using later in this lesson. Watch both videos and then answer the questions below.

Now you will plan a controlled experiment. A controlled experiment is one that has a single independent variable, a single dependent variable, and all other variables held constant (controlled).

You may choose any one of the following as your independent variable: initial water amount, water temperature, can volume (if different size cans are available), or the amount of time the can is left on the hot plate. Percent crush will be the dependent variable for every experiment as that is what is being measured.

Remember whatever independent variable you choose that all other variables must be held constant. For example: if you decide to manipulate the water temperature (in the bucket), that is the only variable that can be manipulated. So in this particular experiment, the initial water amount, the can volume, and the amount of time the can is left on the hot plate must be constant in every trial conducted.

Your experiment must consist of nine trials, three trials for each data point. You will then calculate the average of the three trials at each data point. So using the above example of changing the water temperature, your group would need to conduct three trials using an ice bath, three trials using room temperature water, and three trials using hot water (while measuring the actual temperature of each for each trial).

In order to begin, your group must successfully crush a can and measure all of your variables including: initial water amount, water temperature, can volume (if different size cans are available), and the amount of time the can is left on the hot plate. These settings should be used as constants for all variables that are not your independent variable in each and every trial.

Use your experimental design on page 2 to complete three trials for each data point you are testing for your independent variable.

In order to measure the volume of each can you will need to fill it with water, then measure that amount of water using a graduated cylinder. This measurement should be taken before (initIal volume) and after (final volume) each can crush trial.

The formula to use for percent crush is:

If your group makes any known errors during a trial, you should consider that trial an outlier and complete it again.

In order to determine the relationship between your independent and dependent variable, you will need to create a graph. In order to create a graph within this interface, we will employ the same online data analysis platform we utilized in Lesson 3 called CODAP. Below, you will see a CODAP workbench.

1. The platform is below these instructions. Start by typing your independent variable in the table where it currently reads "Replace with Independent Variable". (Your independent variable is one of the following: initial water amount, water temperature, can volume, or amount of time the can is left on the hot plate.)
2. In order to create a graph, drag your independent variable to the x-axis of the plot as shown in the GIF on the right; the example GIF uses water temperature as an independent variable.
3. Drag the % Crush variable to the y-axis of the plot as shown in the GIF on the right.
4. Observe the resulting plot. Then answer the questions below the CODAP workbench.

In lesson 4, we learned how to identify trends in a graph of two variables for both a direct relationship and an inverse relationship.

But what if your graph doesn't clearly exhibit either of the relationships in the graphs shown above? There is another possibility that we have yet to discuss, that is two variables exhibiting no relationship. If adding a trendline to your data displays a line with a slope close to zero (a horizontal line), then your variables are said to have a no relationship. A graph of two variables (A and B) with a no relationship is shown below.

You will now use a simulation to help determine the reliability of the data your lab group acquired during class.

Experiment with the simulation by manipulating any of the variables (initial water amount, water temperature, or can volume). Be sure to hit "setup" after adjusting these variables or the change will not be reflected in the simulation. Also consider amount of time the can is left in the fire as a variable.

After you feel you have learned all the features of the simulation move on to answer the questions below:

Use your experimental design on page 2 to complete three trials for each data point you are testing for your independent variable using the simulation below.

We will again utilize CODAP to create a graph of your simulation data.

1. Start by typing your independent variable in the table where it currently reads "Replace with Independent Variable". (Your independent variable is one of the following: initial water amount, water temperature, can volume, or amount of time the can is left in the fire.)
2. In order to create a graph, drag your independent variable to the x-axis of the plot as shown in the GIF on the right; the example GIF uses water temperature as an independent variable.
3. Drag the % Crush variable to the y-axis of the plot as shown in the GIF on the right.
4. Observe the resulting plot. Then answer the questions below the CODAP workbench.

Throughout the KMT unit, we have been presented with experiments that involve the following variables: temperature, volume, pressure, and number of particles. The Can Crusher is not different in this aspect. Temperature in our experiment is seen both in the water temperature, and in the amount of time the can is left on the fire. Volume is seen in both the can volume and in the measurement of percent crush. The number of particles is seen in the initial water amount added to the can to start the experiment, and finally, pressure is obviously a factor (though not measured directly) throughout the experiment.

What is different in the Can Crusher experiment is that none of the variables (temperature, volume, pressure, or number of particles) are actually held constant throughout the experiment. In this case, identifying a simple relationship between two variables is impossible. In other words, the can crushing cannot be explained by simply stating that as pressure increases, volume decreases. The temperature was not held constant and neither were the number of particles in the can (the can remains open to the air as it is being heated, so particles in the can are allowed to escape). Stating that as temperature decreases, volume decreases cannot explain the entire phenomenon either as pressure is also changing through the experiment.

Explaining the can crush will require that you focus on what particles are doing on a microscopic level throughout the entire process. The can crush simulation includes a check box labeled "see-inside"; the simulation is included again below so you can perform a trial (or trials) while this box is checked. Be sure to observe the particles in the can throughout the entire can crush, then answer the questions below.