S2.2.1—Collecting data
- Syllabus
- First assessment 2025
- Objective
- S2.2.1
- Level
- HL
Record Experimental Data
Record what happened, not what was expected
Capture relevant qualitative observations alongside sufficient quantitative readings. Qualitative evidence may explain a change, threshold or anomaly; quantitative evidence establishes the size and spread of the relationship.
| Record | Include | Why it matters |
|---|---|---|
| Raw data table | Variable names, units, instrument resolution/uncertainty and unrounded readings | Preserves the original evidence for later processing |
| Repeats | Every reading, not only the mean | Reveals spread and possible anomalies |
| Qualitative observation | What was seen, heard or changed, linked to the relevant reading | Provides context for interpreting the numbers |
| Collection issue | What occurred, when, affected values and action taken | Makes a repeat, correction or exclusion auditable |
Address issues while preserving the evidence
If a sensor saturates, a timing event is missed or the setup changes, pause and check the method. Repeat the affected measurement under the stated conditions when possible, but keep the original entry identified rather than silently replacing or adjusting it.
Use consistent precision
Record to the precision supported by the instrument and keep units explicit. Enough data means sufficient range, spacing and repeats to reveal the relationship—not a large table of duplicated or invented values.
S2.2.1 Exam Analysis
Assessment in practice
1 marksHow it is assessed
Questions ask learners to plot a missing data point accurately.
Command terms
Draw
What earns marks
Place the point at the correct coordinates within the stated plotting tolerance and preserve the graph’s scale.
Watch for
Plotting the point in the wrong quadrant or ignoring the graph scale.
Retrieve Data Evaluation
Record before judging
Keep qualitative observations, labelled quantitative data, units and uncertainty visible.
Test the model
Use the graph shape, intercept, fit, error bars and repeats to decide whether a relationship is supported and whether errors are random or systematic.