Data handling turns a question into evidence: define the group of interest, collect relevant observations, classify them, record frequencies and interpret the results. Categories describe types; numerical data measure or count quantities. A representative sample should reflect the population, not only the easiest people to ask.
| Display | Useful for | Limitation to remember |
|---|---|---|
| Frequency table | Exact counts by value or category | Patterns may be less immediate than in a graph. |
| Bar graph | Comparing categories; separate bars | Check the baseline and equal bar widths. |
| Pictogram | A quick visual comparison | Read the key; a partial symbol represents part of its value. |
| Line graph | Changes over ordered times | Joining categories without meaningful order can mislead. |
| Pie chart | Parts of one whole | Harder to compare small differences or different sample sizes. |
Example
A travel survey records bus \(12\), walk \(8\), car \(4\), total \(24\). A pictogram key of one symbol for four pupils requires three, two and one symbols. The bus sector in a pie chart is \(\dfrac{12}{24}\times360^\circ=180^\circ\).
Asking only pupils at the bus stop would bias this survey towards bus users. A bar axis beginning at \(7\) makes counts \(8\) and \(12\) appear much more different than their actual ratio \(12:8\). Describe the scale distortion, not merely that the chart “looks wrong”.
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