IA idea · Modelling with functions
Does a pendulum's period really depend on the square root of its length?
Research question
Is the relationship between a pendulum's length and its period a power law with exponent ½, and at what swing angle does the simple model stop working?
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Why it makes a good exploration
The textbook formula T = 2π√(L/g) assumes small swings. Testing the exponent with a log-log plot and then pushing the angle until the model fails gives two linked questions with clear answers.
The mathematics you'll need
- Power models y = axⁿ
- Log-log linearisation and regression
- Percentage error and uncertainty
- Estimating g from the fitted constant
Modelling the data, step by step
This idea usually needs a power model. See it worked step by step, with a criterion tip at every step: Power y = a·xⁿ (log–log).
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Where the data comes from
Build a pendulum with 8+ lengths, time 10 swings three times each; use phyphox's pendulum or acceleration tools for precise timing.
- phyphox (RWTH Aachen) — Free app that turns your phone's accelerometer, microphone, barometer and gyroscope into data loggers with CSV export.
- Tracker video analysis — Free tool to track an object frame by frame in a video and export its x–y coordinates.
A possible outline
- Explain the model and its small-angle assumption.
- Collect periods for a range of lengths.
- Plot ln T against ln L; fit a line and interpret the gradient and intercept.
- Estimate g and compare with 9.81 m s⁻².
- Repeat at larger angles and find where the error exceeds 1%.
Pitfalls that cost marks
- Timing single swings (reaction-time error dominates).
- Measuring length to the top of the bob instead of its centre.
- Reporting g without an uncertainty.
Showing personal engagement
- Predict the exponent before you collect data.
- Use a playground swing as a real-world test of your model.
- Explain the large-angle correction you observe.
See Criterion C: personal engagement for what examiners look for.
Which course is it for?
| Course | Fit | Maths to lean on |
|---|---|---|
| AA SL | Good fit | Power models y = axⁿ; Log-log linearisation and regression |
| AA HL | Fits, but add an HL technique | Power models y = axⁿ; Log-log linearisation and regression |
| AI SL | Good fit | Power models y = axⁿ; Log-log linearisation and regression |
| AI HL | Fits, but add an HL technique | Power models y = axⁿ; Log-log linearisation and regression |
Level: Accessible. A good first extended piece of maths, with room to go deeper. See how the IA differs between AA and AI, SL and HL.
How this idea reaches the top bands
Reflection (D)
For this idea, start with the weak points: timing single swings (reaction-time error dominates); and measuring length to the top of the bob instead of its centre. Say how each one affects your answer.
Use of mathematics (E)
SL: power models y = axⁿ; log-log linearisation and regression; percentage error and uncertainty; estimating g from the fitted constant, each explained in your own words and carried out correctly.
How modelling explorations reach the top bands in general: Modelling with functions IA ideas. Guides: A · B · C · D · E · self-grade sheet.
Taking it further
HL: compare the measured large-angle periods with the series correction T ≈ 2π√(L/g)(1 + θ₀²/16).
Extending it for HL
Add an HL technique the question genuinely needs: what an HL modelling exploration adds.
See a complete IA, marked
Should I lease or buy my first car? (AI SL) is a complete modelling exploration, marked on every criterion.
Frequently asked questions
Which IB Maths course is this IA idea for?
It works for AA SL, AI SL, AA HL and AI HL. We rate it Accessible: a good first extended piece of maths, with room to go deeper.
What mathematics does this IA use?
Power models y = axⁿ, log-log linearisation and regression, percentage error and uncertainty and estimating g from the fitted constant.
Where can I get data for this IA?
Build a pendulum with 8+ lengths, time 10 swings three times each; use phyphox's pendulum or acceleration tools for precise timing. Checked sources and tools: phyphox (RWTH Aachen) and Tracker video analysis.
Turn this idea into your IA
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