Data Handling and Representation
Every question in this topic starts the same way: you're handed a messy list of raw data and asked to do something useful with it. The skill being tested isn't arithmetic — it's judgement. Can you organise the mess into a table without miscounting? Can you pick the right picture for the data type in front of you? And can you read that picture back correctly, including spotting when there's a tie for the mode or a class interval with an odd width? Examiners recycle these exact traps every year.
Overview: The Shape of This Topic
Data handling in MYP 2 is a pipeline: raw data → organised table → visual display → interpretation. Every subtopic below is one link in that chain. Get the organisation step wrong (miscount a tally, misclassify discrete vs continuous) and every step after it is wrong too, even if your arithmetic is perfect.
- Raw data is just a list — hard to spot patterns in, easy to miscount.
- Frequency tables and tally charts organise raw data into counts.
- Bar charts, line graphs and pie charts turn those counts into pictures suited to different purposes.
- Stem-and-leaf diagrams and dot plots are the middle ground: organised like a table, but no individual value is lost.
- The whole topic hinges on correctly identifying whether your data is discrete, continuous, or categorical — that single decision drives every choice after it.
The shape of the chapter
Command terms examiners use in this topic
| Command term | What it demands | AO | Mark-earning move |
|---|---|---|---|
| State / Identify | Give a short, direct answer — a value, category or feature — with no working required. | Criterion A | Naming the wrong feature (e.g. giving a frequency when asked for the value itself) forfeits the mark even if your counting was correct. |
| Construct / Complete | Build a full, correctly labelled table or diagram from raw data. | Criterion B | Missing tally marks, an unlabelled axis, or no key on a stem-and-leaf loses a mark even when your frequencies are right. |
| Calculate | Carry out an arithmetic procedure and give the numeric result. | Criterion B | Markers want to see the method (e.g. total − known values); a bare final answer with no working can lose the method mark if it's wrong. |
| Compare | State how two values or categories relate, using the data as evidence. | Criterion D | Just restating both numbers side by side without saying which is bigger and by how much/what factor earns zero. |
| Explain | Link a feature of the data to a real consequence or decision, using 'because'. | Criterion D | Describing what the table shows without saying how it helps the decision scores no marks — the causal link is the mark. |
Key point
Overview