• Review the common class procedure established in activity 3.1.

• Discuss the Carnival Challenge Data Sheet and how to fill out the table. Fill out data collection table headings and units on the Carnival Challenge Data Sheet

  • Suggested headings:

    • Launch Number

    • Pressure (psi)

    • Projectile Placement

    • Landing Position (x,y)

    • Observations

• Emphasize the importance of units on the data table

• Review plotting on graph paper as necessary 

• Make sure students are following proper experimental and safety procedures. 

• Using the common procedure, students will launch the projectile 10 times per group, and plot the landing sites on their graph paper.

  • Make sure students and student groups take turns launching the catapults and that all students are recording the data on the data collection sheet.

  • Once students have completed all their launches, they should transfer their results to the large graph paper poster.

Have the students share their new launch data, and lead discussion about it.

•  Is the data from Trial #2 data is more consistent than from Trial #1?  

  • Why? (Because we were all following the same procedures.) 

• What are other sources of data variability? Some possibilities are listed below:

  • Operator/ Human Error: Things like imprecise measurement, imprecise pressure, and imprecise projectile placement.

  • Machine Error: Does each catapult operate exactly the same as the others? Do they all operate consistently every time? All manufactured parts have a tolerance, which is a range of acceptable dimensions. Not all parts on the catapults are the same size if you measure accurately enough!

  • Random Error: Other environmental factors, like changes in temperature, a gust of wind due to the air conditioning, etc. 

• How can we characterize data variability?

  • Accuracy: How close we are to a desired target? 

    • This is relevant if you are trying to hit the same target repeatedly.

  • Precision: How repeatable is your experiment? 

    • If your data points are highly variable, or very spread out, your data is not very precise. If all your data is clustered closely, you are seeing evidence of precision or repeatability.

• What do we mean by uncertainty?

  • Uncertainty prevents us from making perfectly accurate predictions, even when we control as many variables as possible.

Summary: We have now characterized the performance of the catapults under standard operating procedures. This data can be used to help us design our targets and meet the design requirements given to us by the carnival director.