Topic 1.3: Nerf Car Racing: Turning Data Into an Evidence-Based Claim

Collecting the numbers is only half the job. The more interesting question is what you do with them: how do you turn a table full of stopwatch times into an actual, defensible answer to "which car is faster"?

The first step is finishing the math — calculating average velocity (displacement divided by time) for each measured segment of the track, and also for each full run. With four trials per car, you don't just want one number; you want to see whether those four numbers cluster tightly together or scatter all over the place. Tight, consistent trials are much stronger evidence than a single standout run, because they show the result wasn't a fluke.

From there, a graph makes the comparison visible in a way a table of numbers can't. Plotting average velocity across each interval of the track — or plotting position versus time for a representative run of each car — lets you see at a glance whether a car sped up, slowed down, or held a steady pace, and how the two cars actually stack up against each other.

The last, and maybe most important, piece is being honest about error. No measurement is perfect: a stopwatch has human reaction-time lag built in, a launcher might push slightly differently from run to run, a floor might not be perfectly level. Naming a specific source of error — and thinking about how it might have skewed the result — isn't admitting the experiment failed. It's what separates a scientific claim ("Car A is faster, and here's the evidence and its limitations") from a guess dressed up as a fact. That combination — a claim, backed by data, with an honest account of its limitations — is exactly the kind of reasoning real scientific arguments are built on.

Videos

This is a hands-on analysis and presentation day — no video assigned. The skills here (using data to justify a claim, and identifying sources of error) carry through the rest of the unit and show up throughout AP-style free-response questions.

Try It Yourself

This was a lab analysis and presentation day, so instead of a written problem set, here are the same questions the class worked through with their own data:

1. If Car A won 3 out of 4 races against Car B, is that solid proof Car A is the faster car? What additional information would make you more confident — or less confident — in that conclusion?
2. A friend says, "My car won the very first race, so it's the faster car." Explain in 2-3 sentences why that's not strong evidence, and what would make it stronger.
3. If four trials of the same car give very different times, what does that suggest about the setup or measurement process, rather than about the car itself?
4. Name one specific thing that could introduce error into a toy-car timing experiment (think about the stopwatch, the launcher, the floor, or the person recording data), and explain how it might make a car look faster or slower than it really is.
5. Between a bar graph of average velocity by track segment and a position-vs-time graph of a single run, which one would better show whether a car sped up over the course of its run? Explain your choice.