Introduction to Evaluation, Improvements, and Safety

Welcome to the final stage of your practical journey! You have planned your experiment, taken your readings, and processed your data. Now comes the most critical part for a scientist: evaluation. This isn't just about spotting mistakes; it’s about looking at your method with a critical eye to see how reliable your results are, how they could be better, and how to stay safe while doing it.

In the Unit 3 exam, you will often be asked to criticise a student's method or suggest improvements. Don't worry if this feels a bit like being a detective—once you know what clues to look for, it becomes much easier!

1. Evaluating the Procedure

Evaluation is the process of looking at your results and deciding how much you can trust them. In your exam, you might be given a set of results from an "inexperienced student" and asked to find the flaws.

Spotting Systematic Errors

A systematic error is one that follows a pattern—usually because something is wrong with the equipment or the setup. The best way to spot this is by looking at a graph:

  • If your theory says the graph should be a straight line through the origin (e.g., Hooke’s Law: \(F = k\Delta x\)), but your best-fit line misses the origin, you likely have a systematic error.
  • Zero errors are a common type of systematic error. For example, if a micrometer screw gauge doesn't read \(0.00 \text{ mm}\) when fully closed, every single reading you take will be wrong by that same amount.

Judging Accuracy

Accuracy is how close your calculated value is to the true value (the "accepted" value found in textbooks). You can check accuracy in two ways:

  1. Does the "accepted value" fall within your uncertainty range? (e.g., if you found \(g = 9.7 \pm 0.2 \text{ m s}^{-2}\), then the accepted value of \(9.81 \text{ m s}^{-2}\) is inside your range).
  2. Is the percentage difference between your value and the accepted value less than 5%? If yes, we generally say the result is accurate.

Quick Tip: Remember that Precision is about how close your repeat readings are to each other, while Accuracy is about how close you are to the "right" answer!

2. Suggesting Realistic Improvements

When an exam question asks you to improve an experiment, they want specific, realistic changes, not just "be more careful."

Upgrading the Apparatus

Sometimes the tool isn't right for the job. Consider these upgrades:

  • Measuring length: Instead of a standard ruler (resolution \(1 \text{ mm}\)), use vernier calipers (resolution \(0.1 \text{ mm}\)) or a micrometer screw gauge (resolution \(0.01 \text{ mm}\)) for small objects like wire diameters.
  • Timing: Human reaction time is about \(0.2 \text{ s}\). If you are timing something very fast (like a falling ball in Core Practical 1), use light gates connected to a data logger to remove reaction time error.
  • Temperature: Use a digital thermometer or a temperature probe for better resolution and to see quick changes.

Refining the Technique

How you use the tools matters just as much as the tools themselves:

  • Parallax Error: Always state that you will view scales at eye level. In experiments involving springs or pendulums, use a fiducial marker (a clear reference point, like a needle) to mark exactly where to start/stop measurements.
  • Controlling Variables: If you are measuring the resistance of a wire (Core Practical 7), the wire might get hot, which changes its resistance. Improvement: Turn off the circuit between readings to keep the temperature constant.
  • Reducing Random Effects: If a measurement is hard to take (like the diameter of a wire), take readings at different orientations and at various points along the wire, then calculate a mean.

Key Takeaway: Always explain why the improvement helps. Don't just say "use a micrometer"; say "use a micrometer to reduce the percentage uncertainty in the diameter measurement."

3. Health and Safety

Safety is a major part of Unit 3. You must be able to identify risks and suggest precautions. Here are the most common ones for your Core Practicals:

Mechanical Safety (Core Practicals 1, 2, and 3)
  • The Risk: Heavy masses falling on feet or wires snapping and hitting eyes.
  • The Precaution: Use a catch box filled with sand or foam under falling objects. Wear safety goggles when stretching wires under high tension (Young Modulus).
Electrical Safety (Core Practicals 7 and 8)
  • The Risk: Wires getting hot enough to cause burns or components melting.
  • The Precaution: Use low voltages and currents. Switch off the power supply when not taking readings.
Light and Lasers (Core Practical 6)
  • The Risk: Laser light can permanently damage the retina (eyes).
  • The Precaution: Do not look directly into the beam. Place a warning sign on the door. Ensure there are no reflective surfaces (like watches or jewelry) that could bounce the beam into someone's eye.

Did you know? A safety precaution is only useful if it directly addresses a risk in that specific experiment. Forgetting your goggles in a circuit experiment is bad practice, but mentioning it in an exam won't get you marks unless there's a risk of something "snapping" or "splashing"!

4. Wider Context: Benefits and Risks

The syllabus mentions the "implications of the physics." This means understanding how the experiment relates to the real world.

Example: The Young Modulus (Core Practical 3)
- Benefit: Engineers need to know the Young Modulus of steel to ensure a bridge can support weight without deforming permanently (plastic deformation).
- Risk: If the material is used beyond its elastic limit, the structure could fail unexpectedly.

Example: Resistivity (Core Practical 7)
- Benefit: Designing efficient power cables. We want materials with very low resistivity (like copper) to reduce energy wasted as heat.
- Risk: High currents in cables with high resistivity can cause fires.

Summary Checklist for the Exam

When you are asked to evaluate an experiment, run through this mental list:

  • Zero errors: Did they check the instruments before starting?
  • Parallax: Did they use a fiducial marker or view at eye level?
  • Variables: Did they keep "other" factors (like temperature) constant?
  • Resolution: Was the equipment sensitive enough for the size of the measurement?
  • Safety: Did they protect themselves from the specific hazards of the setup?
  • Graph: Does the best-fit line go where it’s supposed to? If not, why?

Don't worry if this seems tricky at first! Evaluation is a skill that grows with practice. Every time you read a core practical, ask yourself: "What could go wrong here, and how would I fix it?"