Working with Sets of Data
Compare datasets using IQR, outliers and statistical measures in context. MYP Year 5 Standard Maths statistics guidance for Criterion D responses.
Building on Basic Statistics
Once you can calculate measures for a single dataset, the next step is comparing two or more datasets. This topic develops your ability to evaluate data critically and draw meaningful conclusions — skills that are directly assessed in Criterion D.
Interquartile Range (IQR)
The interquartile range (IQR = Q3 − Q1) measures the spread of the middle 50% of data. Unlike the range, it is not affected by extreme values, making it a more reliable measure of consistency.
You need to be able to:
- Calculate Q1, Q3, and IQR from ordered data
- Use IQR to compare the spread of two datasets
- Explain what a larger or smaller IQR means in context
Identifying Outliers
An outlier is a value that lies significantly outside the general pattern of a dataset. In MYP assessments, you may be asked to identify outliers using the IQR fence method or simply by inspection of a box plot. Always consider whether an outlier reflects a genuine anomaly or a data entry error.
Comparing Datasets in Context
When comparing two datasets, structure your response around:
- A comparison of averages (e.g. "Dataset A has a higher median, suggesting…")
- A comparison of spread (e.g. "Dataset B has a larger IQR, indicating more variation…")
- A conclusion in context (e.g. "This suggests students in Group B performed less consistently…")
This three-part structure is what Criterion D responses reward.
Common Mistakes
- Stating the IQR without interpreting what it means
- Comparing means when the data is skewed — the median is often more appropriate
- Ignoring outliers rather than acknowledging them in conclusions