Interpret results and evaluate the method
Describe patterns, draw evidence-based conclusions, recognise anomalies and suggest targeted improvements.
Cambridge International Biology 9700, 2028–2030. Paper 3 assesses practical skills in a supervised laboratory; these lessons support preparation but do not replace safe, supervised laboratory experience.
Before you begin
- Use biological vocabulary and basic calculations from the AS Biology course. Follow your school laboratory rules and teacher instructions for all practical work.
Work on paper. Try each question before revealing help, and explain why your method works.
Quick readiness check
What makes an improvement well targeted?
What you will learn
- Distinguish a pattern from an explanation.
- State whether results support a hypothesis and qualify confidence.
- Link a source of error to a relevant improvement.
Describe before explaining
Quote the direction and important features of a trend, using data values where useful. A conclusion summarises what the results show; an explanation links that pattern to biological ideas.
State whether the hypothesis is supported, partly supported or not supported, and refer to the evidence. Do not claim causation or generality beyond the design and measurements.
Improve the source of error
Random error can create scatter; systematic error can shift readings in one direction. Identify the likely source in the actual method before proposing an improvement.
Useful improvements are specific: repeat measurements and calculate a mean, use smaller intervals, improve measurement resolution, standardise a variable more effectively or extend the range. An extension tests a new question rather than repairing the current method.
Pause and explain
A response says “repeat the experiment” after identifying noisy single readings. Why is this relevant?
Worked example
Three repeats at each temperature vary widely. Give one conclusion limit and one improvement.
Show the worked solution
- The spread reduces confidence in the mean trend.
- Collect more repeats or refine the measurement method.
- Do not discard an inconvenient value without a justified rule.
Answer The trend is less certain because repeat values vary widely. Collect more replicates and check the measuring method; investigate any anomalous value before deciding whether it should be excluded.
From guided practice to a new situation
Write your answer and reasoning first. Use a hint only if you are stuck. The model solution is for self-checking; your written work is not automatically marked.
Rates rise from 2.0 to 4.1 to 6.0 units, then fall to 3.2 at the last value. How should you handle the last result?
Give me a hint
Identify its relation to the pattern but do not delete it automatically.
Compare my reasoning
- Describe the increase through the first three values.
- Flag the final value as potentially anomalous.
- Check the method, retain it unless an exclusion rule is justified, and discuss its effect.
The final value appears anomalous relative to the preceding rise. Check for a recording or procedural cause; do not remove it without justification, and explain how it affects confidence in the conclusion.
Look for these in your work
- Pattern described
- Anomaly handled cautiously
- Confidence considered
A thermometer reads 2 °C too high throughout. Is this random or systematic error, and what improvement helps?
Give me a hint
Consider whether repeated readings shift in the same direction.
Compare my reasoning
- A consistent offset is systematic error.
- Calibrate or replace the thermometer and repeat affected measurements.
This is a systematic error. Calibrate the thermometer against a suitable reference or use a correctly calibrated instrument.
Look for these in your work
- Error type classified
- Improvement addresses source
The range of the independent variable is too narrow to show where the response plateaus. Suggest an extension.
Give me a hint
Keep the existing method, but add values that answer a new part of the question.
Compare my reasoning
- Extend the independent-variable range beyond the current values.
- Use suitable intervals and repeat measurements in the new range.
Collect additional repeated measurements at higher independent-variable values to determine whether and where the response plateaus.
Look for these in your work
- Extension distinguished from repair
- New values and repeats proposed
Common mistakes
- Saying “the experiment was inaccurate” without naming the source.
- Treating an anomaly as an error that must be deleted.
- Claiming a hypothesis is proven.
What can you explain now?
What makes an improvement well targeted?
Compare with the explanation
It addresses a named weakness in the method
A specific change should reduce the identified error.
After trying it yourself, choose your next review. This is your self-assessment.
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Make it stick
How do you connect a named source of error to a useful improvement?
If you needed the solution, close it and solve the problem again from a blank page. A correct answer is stronger when you can explain the reason for each step.