| Lesson Plan |
| Grade: |
Date: 25/02/2026 |
| Subject: Physics |
| Lesson Topic: understand that fluctuations in count rate provide evidence for the random nature of radioactive decay |
Learning Objective/s:
- Describe the random, independent nature of radioactive decay.
- Explain why count‑rate fluctuations follow a Poisson distribution.
- Calculate the mean count and standard deviation from experimental data.
- Compare measured fluctuations with the Poisson prediction and discuss possible sources of discrepancy.
- Apply the relation σ/⟨n⟩ = 1/√⟨n⟩ to predict how fluctuations change with count rate.
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Materials Needed:
- Geiger‑Müller tube with counter interface
- Weak radioactive source (e.g., ⁶⁰Co or ⁹⁰Sr)
- Computer with projector
- Simulation software or spreadsheet for random decay modelling
- Worksheet with data table and calculation prompts
- Calculator
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Introduction:
Begin with a striking image of a Geiger counter clicking rapidly, asking students what determines the irregular pattern of clicks. Recall their prior study of exponential decay and half‑life, emphasizing that each nucleus decays independently. Explain that today they will see how this randomness produces measurable fluctuations and that they will be able to predict the size of those fluctuations.
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Lesson Structure:
- Do‑now (5'): Quick quiz on exponential decay and half‑life.
- Mini‑lecture (10'): Review stochastic decay, introduce Poisson statistics and derive σ = √⟨n⟩.
- Demonstration (15'): Set up the Geiger‑Müller tube, record counts for ten 10‑second intervals, fill the data table.
- Data analysis (10'): Students compute mean, σ, compare with Poisson prediction, discuss detector efficiency and background.
- Simulation activity (15'): Use a computer program to generate random decay counts for different sample sizes; observe the distribution approaching Poisson.
- Guided discussion (5'): Link experimental and simulated results to the concept of randomness.
- Exit ticket (5'): Write one sentence summarising how count‑rate fluctuations provide evidence of stochastic decay.
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Conclusion:
Recap that the spread of counts is an intrinsic property of radioactive decay, not merely experimental error, and that σ = √⟨n⟩ quantifies this randomness. Highlight how increasing the count rate reduces the relative fluctuation, reinforcing the 1/√⟨n⟩ dependence. For homework, assign a new data set for students to analyse and predict the expected σ, preparing them for the next lesson on radiation safety applications.
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