Interpreting Statistical Data
9.2 Interpreting Statistical Data – Cheat Sheet
1. Reading and interpreting data
- Identify key information from tables, charts, and graphs (bar charts, pie charts, line graphs, histograms, scatter diagrams)
- Look for highest, lowest, and most common values
- Recognise trends (increasing, decreasing, constant)
- Note units and scales before interpreting
2. Drawing inferences
- Use the data to make logical conclusions (e.g. “Boys are generally taller than girls in this sample”)
- Avoid making over-generalisations (sample data may not represent the entire population)
3. Comparing sets of data
| Measure | Purpose | Example |
|---|---|---|
| Mean | Shows central value | Class A mean height = 165 cm, Class B mean = 170 cm |
| Median | Middle value | Less affected by extreme values |
| Mode | Most frequent value | Mode shoe size = 8 |
| Range | Spread (max − min) | 185 − 150 = 35 cm |
| Interquartile Range (IQR) | Spread of middle 50% | Q₃ − Q₁ |
4. Using tables for comparison
| Class | Mean Height (cm) | Median Height (cm) | Range (cm) |
|---|---|---|---|
| A | 165 | 166 | 35 |
| B | 170 | 169 | 28 |
Conclusion: Class B is slightly taller on average and has less variation in height.
5. Restrictions on conclusions
- Data may be biased (sample not random)
- Sample size may be too small
- Data might be outdated or incomplete
- Correlation does not imply causation (two things can be related without one causing the other)