Australian Curriculum v9 / ACiQ Year 9 Science - Unit 1 - Validity, reliability and uncertainty

Validity, Reliability and Uncertainty | Year 9 Science

Evaluate whether investigation evidence is trustworthy by separating validity, reliability and uncertainty.

Updated 2026-06-15 - 4 min read

Science conclusions are only as strong as the evidence behind them. In Year 9, you begin evaluating evidence more carefully by separating three ideas: validity, reliability and uncertainty.

These words are often mixed up. Keeping them separate makes investigation writing much stronger.

Validity: did the test measure the right thing?

An investigation is valid when the method is suitable for the question. The independent variable should be changed deliberately, the dependent variable should be measured appropriately, and important controlled variables should be kept the same.

Question: How does ramp height affect toy car speed?

A valid method would change ramp height and measure speed in a consistent way. It would control car type, ramp surface, release method and distance.

If one trial uses a wooden ramp and another uses carpet, the method becomes less valid because ramp height is not the only important difference.

Reliability: would the result happen again?

Reliability is about consistency. Repeated trials, larger sample sizes and careful measuring can improve reliability.

If a plant growth investigation gives results of 8 cm, 9 cm and 8.5 cm for the same condition, the results are fairly consistent. If the results are 3 cm, 14 cm and 8 cm, something may be inconsistent in the method or measurement.

Uncertainty: measurements are not perfect

All measurements have limits. A ruler with millimetre markings cannot measure exact length to infinite precision. A stopwatch may include reaction time delay. A digital scale may round to the nearest gram.

Uncertainty does not mean the data is useless. It means the claim should match the precision of the evidence.

If two results are 10.0 cm and 10.1 cm, the difference may not matter if the measurement uncertainty is about 0.1 cm. If the results are 10 cm and 18 cm, the difference is more convincing.

Claims should match evidence

A strong science conclusion does not overclaim. It uses cautious language when the evidence is limited.

Weak: "Fertiliser always makes plants grow faster."

Stronger: "In this investigation, plants given fertiliser grew more on average than plants without fertiliser, but the sample size was small and light exposure was not fully controlled."

The stronger conclusion still identifies a pattern, but it also recognises limitations.

Mean values still need judgement

Calculating a mean can make repeated results easier to compare, but it does not automatically make the data reliable. If one result is very different from the others, ask whether it is an outlier and whether there is a method reason for it.

For example, results of 12 s, 13 s and 28 s should not be averaged without comment. The 28 s trial may show a real issue, but it may also come from a timing or equipment mistake.

Improving an investigation

Useful improvements match the problem.

If validity is weak, control a confounding variable or improve the method.

If reliability is weak, repeat trials, increase sample size or standardise technique.

If uncertainty is high, use a more precise measuring tool or a clearer measurement rule.

Quick check

  1. Which word describes whether the method tests the intended relationship?
  2. Which word describes consistency across repeats?
  3. Name one source of uncertainty when timing a race by hand.
  4. Why is "my hypothesis was right" not a full conclusion?

Answers:

  1. Validity.
  2. Reliability.
  3. Human reaction time when starting or stopping the stopwatch.
  4. A conclusion should describe the evidence, pattern and limitations, not just whether the prediction matched.

Transfer task

Choose a practical investigation you have done. Write one sentence each about validity, reliability and uncertainty. Then suggest one improvement that matches the weakest part of the method.

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