What to Expect

Activity 1 | Overview

The principle of science, the definition, almost, is the following:
The test of all knowledge is experiment. Experiment is the sole judge of scientific ‘truth’.
– Richard Feynman

Scientific ideas live or die by experiment. Yet experimental work is often messy, even when the system itself is simple. It demands preparation, care, patience and attention to detail.

Learning how to plan, carry out and interpret an experiment builds essential skills, whether you aspire to be a theorist or do not intend to pursue science as a career. It develops intuition, sharpens judgement, and teaches respect for the gap between an idea on paper and a scientific claim supported by evidence.

In many teaching labs, for very good reasons, experiments are highly curated and tightly choreographed. However, the aim in 76 is different. The goal is to take more responsibility for what is measured, how it is measured, and what can honestly be concluded from the result.

An experiment is rarely finished when a set of numbers has been collected because we are then confronted with more questions such as:

  • Are these numbers reasonable?
  • How can that be tested?
  • Is there a model that can help interpret them?
  • What uncertainties or hidden errors do they contain?
  • Are they good enough to answer the question being studied?
  • If not, what should be improved?
  • If there are inconsistencies, does the problem lie in the measurement, the model, or both?
  • What assumptions may be hidden in the method or analysis?
  • How could the measurement be made more robust?

The first activity of 76 addresses these issues.

This activity unfolds over three weeks. Each week adds a new layer of sophistication to the same basic system: a simple pendulum.

The aim is not only to collect data, but to learn how measurements become evidence. Across the three weeks, the work will move from first measurements, to comparison of results, to numerical modeling, to improved measurement, and finally to judging how well a model explains the data.

By the end of this activity, it should be possible to:

  • make and record repeated measurements with care
  • judge whether two results are meaningfully different
  • use uncertainty to support a decision
  • compare experimental data with a model
  • improve a measurement when the first result is not good enough
  • use computation as a tool for prediction and interpretation
  • reflect on how much confidence a result deserves

flowchart TD

    A["<span class='xred'>Week 1 (IS)</span><br>**(Experiment)**<br>Compare T<sub>10</sub> with T<sub>20</sub>."]

    BA["<span class='xred'>Week 2 (Lecture)</span><br>**(Model)**<br>Verify experiment."]

    BB["<span class='xred'>Week 2 (IS)</span><br>**(Experiment)**<br>Collect detailed data<br/>to test the model."]
    BC["<span class='xred'>Week 2 (IS)</span><br>**(Experiment, if necessary)**<br>Retake T<sub>10</sub> with T<sub>20</sub><br>"]

    CA["<span class='xred'>Week 3 (Lecture)</span><br>**(Model)**<br>Match model with experiment."]
    CB["<span class='xred'>Week 3 (IS)</span><br>**(Experiment)**<br>Retake data to rectify any issues."]

    A --> BA
    BA --> BB
    BA --> BC
    BB --> CA
    CA --> CB

    %% classDef investigation fill:#e8f1fb,stroke:#27628a,stroke-width:2px,color:#111;
    %% classDef modelling fill:#f5ead7,stroke:#a26721,stroke-width:2px,color:#111;
    %% classDef comparison fill:#e5f3e7,stroke:#347a3d,stroke-width:2px,color:#111;
    %% classDef outcome fill:#f3e5ef,stroke:#8b4778,stroke-width:2px,color:#111;

    %% class A investigation;
    %% class B,C modelling;
    %% class D,E comparison;
    %% class F outcome;

Stages of the pendulum activity I.

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