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Rubber Band Calibration: Experimenting Pennies' Impact on Length - Prof. Cheryl Peterson, Papers of Mathematics

An experiment to investigate the relationship between the length of a rubber band and the number of pennies it supports. Students are instructed to collect data by hanging bags of pennies from a rubber band and recording the length of the rubber band. They then use the data to create a scatter plot and determine the line of best fit, which can be used to estimate the number of pennies based on the length of the rubber band. The document also includes instructions for using the regression line to make estimates and for interpreting the slope of the line.

Typology: Papers

2009/2010

Uploaded on 02/24/2010

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Calibrating a Rubber Band:
Suppose we hang a bag of pennies from a rubber band. If we increase the number of pennies, we would
expect the length of the rubber band to increase.
Is there a (linear) relationship between the length of a rubber band and the number of pennies in a bag?
If so, can we use that relationship to calibrate the rubber band and use it as a device to count pennies or
weigh objects?
Data Collection:
Working in a small group of about 4 people, collect data by hanging a bag of pennies from a rubber band
and recording the length (in centimeters) of the rubber band versus the number of pennies hanging from
it. Start with 20 pennies and add 20 pennies at a time, up to about 100 pennies.
Number of Pennies
N
Length of Rubber Band
L (cm)
20
40
60
80
100
Scatter Plot and “Line of Best Fit” (Regression Line) – by Hand:
Plot your points on the graph paper on the next page, with number of pennies, N, on the horizontal axis
and length of rubber band, L, on the vertical axis. Sketch a line of best fit.
Using the “Line of Best Fit” to Estimate Number of Pennies – by Hand:
Put an unknown number of pennies in the bag, then measure and record the length of the rubber band.
Use the line you drew on the next page to determine (and record) the corresponding number of pennies.
How many pennies are predicted? Now count the pennies. How close was the predicted number to the
actual number?
Length = ____________ , Predicted # pennies = ____________ , Actual # pennies = ____________
.
Linear Models
!Rubber Band Length versus Number of Pennies!MA 104 10-1-09
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Calibrating a Rubber Band:

Suppose we hang a bag of pennies from a rubber band. If we increase the number of pennies, we would expect the length of the rubber band to increase. Is there a (linear) relationship between the length of a rubber band and the number of pennies in a bag? If so, can we use that relationship to calibrate the rubber band and use it as a device to count pennies or weigh objects?

Data Collection:

Working in a small group of about 4 people, collect data by hanging a bag of pennies from a rubber band and recording the length (in centimeters) of the rubber band versus the number of pennies hanging from it. Start with 20 pennies and add 20 pennies at a time, up to about 100 pennies.

Number of Pennies

N

Length of Rubber Band

L (cm)

Scatter Plot and “Line of Best Fit” (Regression Line) – by Hand:

Plot your points on the graph paper on the next page, with number of pennies, N , on the horizontal axis and length of rubber band, L , on the vertical axis. Sketch a line of best fit.

Using the “Line of Best Fit” to Estimate Number of Pennies – by Hand:

Put an unknown number of pennies in the bag, then measure and record the length of the rubber band. Use the line you drew on the next page to determine (and record) the corresponding number of pennies. How many pennies are predicted? Now count the pennies. How close was the predicted number to the actual number? Length = ____________ , Predicted # pennies = ____________ , Actual # pennies = ____________ .

Linear Models

Rubber Band Length versus Number of Pennies MA 104 10-1-

Scatter Plot and Line – by Hand:

Make a scatter plot on this paper for Rubber Band Length, L, versus Number of Pennies, N. Indicate the scale on the vertical axis (you don’t have to start at 0). Does it look like a linear model would be reason- able?

Group Tag Letter

on Bag

Length of

Rubber Band

L

Estimated

of Pennies

N

Actual

of Pennies

A B C D E F G H I

Interpretation of Slope of the Regression Line, L = L ( N ):

Copy your regression line equation (from the preceding page): L = L ( N ) = ___________________________ According to the regression line equation, for each penny we add to the bag, we would expect the length of the rubber band to increase by ____________ centimeters.

Interpretation of Slope of the Line, N = N ( L ):

Copy your equation (from the preceding page) for N = N ( L ) = ___________________________ According to this equation, for each centimeter that the rubber band increases in length, we would expect the number of pennies to increase by ____________ pennies.