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Session 11: Measurement & Data Collection Lab

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Session 11

Measurement & Data Collection Lab

Scaling Up

Session 6 taught you that calipers vary trial to trial.

Today we scale that same idea up into three full measurement experiments.

Today's Setup

Three stations. Three completely different tools.

Today's Setup

  • A spring scale and a set of known weights
  • A yardstick and a ping-pong ball
  • A photoresistor and a multimeter

Today's Setup

This is not a physics lesson about springs, bouncing, or light sensors.

Every station asks the same question: does the reading change the way you'd predict?

Two Words You'll Use All Semester

In any experiment, one thing you change on purpose, and one thing you measure as a result.

Two Words You'll Use All Semester

  • Independent variable (IV) — the one you change on purpose.
  • Dependent variable (DV) — the one you measure, because it depends on the IV.

Three Stations, Three Examples

  • Spring Scale: IV = known weight, DV = scale reading
  • Ping-Pong Drop: IV = drop height, DV = bounce height
  • Photoresistor: IV = lighting combination, DV = resistance

Why This Matters Later

On the Launcher Project, your team picks its own IV — pull distance or launch angle — and every single thing after that is built around the choice.

You'll see "IV" written as shorthand from here on. It always means the thing you're deliberately varying.

The Actual Task

  1. At each station, pick at least 4 different settings (your IV)
  2. For each setting, measure the result (your DV) 3 times
  3. Record every trial in a raw data table — at all three stations

Why 3 Trials, Not 1?

Same reason as Session 6's calipers.

Why 3 Trials, Not 1?

One trial can't tell you if it was typical or a fluke. Three trials start to show you the real spread.

Two Things to Remember

More trials isn't slower science.

It's what makes your data trustworthy instead of lucky.

Two Things to Remember

Write down every trial, not just the "clean" ones.

A weird trial is still real data. Don't quietly leave it out.

A Real Quality-Control Test

Ping-pong ball manufacturers actually run this exact drop test.

A Real Quality-Control Test

Drop from 30 cm (about 12 inches), and the rebound has to land between 24 and 26 cm — or the ball fails inspection.

Same idea as Session 9's tolerance. Same discipline, real product.

Station C: A Different Shape?

At Stations A and B, doubling the input roughly doubles the reading.

Watch what happens at Station C. It might not.

Next Time

Session 12: Functions in Sheets

Move your Spring Scale data into a spreadsheet — and put it to work with real spreadsheet functions.

'F' → Fullscreen

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Build

Step 1: Station A — Spring Scale

Using the weight set your instructor provides, pick at least 4 different known weights to test. For each one, hang it on the spring scale and record the reading. Unhook and re-hang between trials — reading the same hang three times isn't three trials.

Known WeightTrial 1Trial 2Trial 3

Label your units. Every trial gets its own recorded value — not an average.

Step 2: Station B — Ping-Pong Drop

Drop the ball from each marked height — open hand, no push. A partner sights the top of the first bounce, at eye level, against the yardstick. Test all 4 marked heights, 3 trials each.

Drop HeightTrial 1 BounceTrial 2 BounceTrial 3 Bounce

Label your units. Every trial gets its own recorded value — not an average.

Step 3: Station C — Photoresistor + Multimeter

Do not move the sensor between trials — it stays taped down in one spot. Only the switches change. Test all 4 lighting combinations below, 3 trials each — reread the multimeter 3 times per row without touching the sensor.

Lighting CombinationTrial 1 (Ω)Trial 2 (Ω)Trial 3 (Ω)
Both switches off
Switch 1 only
Switch 2 only
Both switches on

Every trial gets its own recorded value — not an average.

Step 4: Compare as a Class

Your instructor will collect one reading from each station on the board.

StationClass LowClass HighRange
Spring Scale
Ping-Pong Drop
Photoresistor

Same room, same tools, same technique — why might one station's range be so much bigger than another's?

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Checkpoint

Before you submit, confirm:

  • All three stations completed, each with at least 4 settings and 3 trials
  • Every trial is recorded individually — no pre-averaged numbers anywhere
  • Units are labeled at every station
  • The class comparison table is filled in
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Reflection

Answer these on your own. Reflections are individual, even when the rest of the session was team work.

  1. Pick one of today's three stations. Name its independent and dependent variable, and explain in one sentence how you'd know which was which if nobody told you.
  2. Session 12 moves your Spring Scale data into Sheets and uses functions to summarize it automatically. Looking across all three of today's tables, which one has the most trial-to-trial disagreement, and which has the least? Why do you think that is?
  3. For the station where your trials agreed with each other most closely, what does that tell you about that tool or setup? For the station where they disagreed the most, what's your best guess as to why?
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Submit

Submit all three raw data tables, the class comparison table, and your reflection.

Activity Complete