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IGCSE Physics, Cambridge 0625, Malaysia

How to Handle Data Questions in IGCSE Physics

How to read tables, interpret data and draw conclusions in Cambridge IGCSE Physics 0625 papers.

Written by IGCSEPhysics Content Team · Physics subject adviser: K. S. Tan, 15+ years teaching IGCSE Physics · Checked against the Cambridge IGCSE Physics (0625) 2026 to 2028 syllabus

Data questions give you a table, a set of measurements or experimental results. They test whether you can extract information, spot patterns and draw conclusions.

Reading the table

Start by reading the column headings and their units. Identify which variable is independent (the one the experimenter changed) and which is dependent (the one that was measured).

Spotting patterns

Look for:

  • Direct proportion: when one variable doubles, does the other also double?
  • Inverse proportion: when one variable doubles, does the other halve?
  • Linear relationship: does the data form a straight line when plotted?
  • No obvious pattern: the variables may not be related.

Using data in calculations

When a question asks you to use the data:

  1. State the values you are using and where they come from.
  2. Substitute into the correct equation.
  3. Show the calculation clearly.
  4. Give the answer with the correct unit.

Anomalous results

If one value does not fit the pattern, identify it and exclude it from your conclusion. State why it might be anomalous (e.g., “This reading may be due to a measurement error or a change in conditions”).

Drawing conclusions

A conclusion must be supported by the data. Use the pattern you identified:

  • “The data shows that as the length of the wire increases, the resistance increases proportionally.”
  • “The results suggest that the current through the resistor is directly proportional to the voltage across it.”

Avoid going beyond the data. If the data covers lengths from 20 cm to 100 cm, do not make claims about 200 cm.

Evaluating reliability

If asked, comment on:

  • Whether repeat measurements were taken
  • Whether the results are consistent (close to each other)
  • Whether there are anomalous results
  • How the experimental method could be improved

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